Wednesday

Transcription

Wednesday

INFORMS Austin – 2010
Wednesday, 8:00am - 9:30am
WA03
2 - Financial Engineering for Refinery Operations: Challenges
and Opportunities
Li Zheng, Professor, Tsinghua University, Department of Industrial
Engineering, Beijing, 100084, China, lzheng@tsinghua.edu.cn
■ WA01
Over the past decade, the world has witnessed the extreme price volatility from
both crude supply and final product market. Financial engineering tools have been
used to hedge the financial risk in refinery operations recently. In this talk, we
present the challenges of the problem and provide some potential ideas for future
research.
C - Ballroom D1, Level 4
Multi-stage Stochastic Optimization Applied to
Energy Planning
3 - Integrated Financial and Operational Model for Crude Oil
Procurement in Refineries
Zhen Liu, Assistant Professor, Missouri University of Science &
Technology, United States of America, zliu@mst.edu, Simin Huang
Sponsor: Energy, Natural Resources and the Environment/ Energy
Sponsored Session
Chair: Steffen Rebennack, Assistant Professor, Colorado School of Mines,
Division of Economics & Business, Boulder, CO, United States of America,
steffen@ufl.edu
1 - Quasi-Monte Carlo Methods for Hydroelectric Energy Planning
Tito Homem-de-Mello, University of Illinois at Chicago, Chicago, IL,
United States of America, thmello@uic.edu, Erlon Finardi,
Vitor de Matos
The world seems to have entered into an era of higher crude oil price volatility. As
the crude oil cost is about 90% of the refinery input cost, there has been significant
volatility in the margins and profitability of any petroleum refinery. An integrated
financial and operational model is developed to hedging the financial risk.
4 - Financial Engineering Model for Crude Transportation in Refineries
Zhihai Zhang, Associate Professor, Tsinghua University, Department
of Industrial Engineering, Beijing, 100084, China,
zhzhang@tsinghua.edu.cn
We study a multi-stage stochastic programming model for hydroelectric energy
planning in Brazil. Sampling techniques are used to generate scenario trees from the
stochastic process defining the water inflows, and also to select scenarios within that
tree. We analyze the use of Quasi-Monte Carlo methods for the problem. We also
discuss statistical performance measures that allow us to compare methods, and
present numerical results to evaluate the effectiveness of the proposed approach.
The crude transportation cost in refineries could be up to several billion dollars and
the volatility of freight rates can be substantial. A decision-making model for
optimal oil tanker selection procedure is developed to help refining companies
manage the freight market risk.
2 - Reservoir Hydropower Operations: Valuing Flexibility
Stein-Erik Fleten, Professor, NTNU Norway, Department of Industrial
Economics and Technology Management, Trondheim, Norway,
Stein-Erik.Fleten@iot.ntnu.no, Martin Prokosh, Camilla Kolsrud
■ WA03
In this talk we provide insights into how storage flexibility impacts the expected
revenue of hydropower plants. Using daily data going back ten years from 14
different hydropower plants with significant seasonal reservoir capacity, and who
operate in a well-functioning market, we conduct an empirical analysis of the
different factors affect the ability of hydropower producers to exploit high prices.
Storage flexibility on average accounts for 22% of actual revenues, ranging from 0
to 40%.
Challenges for the US Biofuels Industry: Economic and
Technological Uncertainties
Sponsor: Energy, Natural Resources and the Environment//Forestry
Sponsored Session
Chair: Hayri Onal, University of Illinois at Urbana-Champaign, Dept
Agricultural and Consumer Economics, Urbana, IL, 61801, United States
of America, h-onal@illinois.edu
1 - Modeling Uncertainty in Biomass Greenhouse Gas Emissions with
the Calculating Uncertainty in Biomass
Aimee Curtright, Physical Scientist, RAND Corporation, Pittsburgh,
PA, 15213, acurtrig@rand.org, Henry Willis, David Johnson,
Costa Samaras
3 - Optimal Control of Energy Storage using the Knowledge Gradient
with Nonparametric Beliefs
Warren Powell, Professor, Princeton University, Sherrerd Hall,
Princeton, NJ, 08544, United States of America,
powell@princeton.edu, Emre Barut
We consider different natural gas and pumped hydro storage problems as stochastic
control problems which can be solved using tunable policies governed by tunable
parameters. We present a novel stochastic search algorithm using the knowledge
gradient adapted to nonparametric beliefs, which produces policies that are easy to
implement. We demonstrate that the logic produces policies that slightly outperform
actual performance.
The greenhouse gas (GHG) intensity of biofuels depends on how feedstocks are
produced, transported, and processed. This paper will describe the Calculating
Uncertainty in Biomass Emissions (CUBE) model, a tool developed for the National
Energy Technology Laboratory to examine uncertainties in bio-feedstock GHG
estimates. The limits on the precision of results, the value of additional emissions
information, and the sources and magnitude of uncertainty will be discussed.
4 - Decomposition Approach for G-T Expansion Planning with Implicit
Multipliers Evaluation
Fernanda Thome, PSR, Rio de Janeiro, Brazil, fernanda@psr-inc.com,
Marcia H.C. Fampa, Luiz Carlos da Costa Jr., Silvio Binato
2 - Ecosystem Costs in a Logistical Model of Cellulosic
Ethanol Production
David Lambert, Professor and Head, Department of Agricultural
Economics, Kansas State University, lambertd@k-state.edu,
Jason Bergtold, Elizabeth Canales
Algorithms solving stochastic hydrothermal operation problems usually take
computational advantages in the elimination of constraints whose explicit
representation does not affect the problem’s optimal solution. This work presents a
new methodology for solving generation-transmission expansion planning problems
based on Benders decomposition technique and the evaluation of the Lagrange
multipliers associated to those non-explicit constraints and required in the
construction of the Benders cuts.
Network models of biomass use for cellulosic ethanol production often ignore
ecosystem opportunity costs. Building upon an existing MIP model, we incorporate
ecosystem opportunity costs arising from soil erosion, loss of organic and inorganic
matter, and carbon sequestration values associated with crop residue and energy
crop harvest for ethanol production.
■ WA02
3 - Strategic Biofuel Supply Chain Planning Under Supply, Demand,
and Technology Uncertainties
Yueyue Fan, University of California-Davis, Davis, CA, 95616, United
States of America, yyfan@ucdavis.edu
Refinery Operations with Spot and Forward Markets
This talk focuses on modeling and computational challenges in strategic biofuel
supply chain planning under supply, demand, and technology uncertainties. Using a
case study based on California settings, the economic feasibility, infrastructure
requirements, and the environmental impact of converting biowastes to fuel are
analyzed.
Cluster: Energy: Modeling the Interface Between Markets and
Operations
Invited Session
Chair: Simin Huang, Tsinghua University, Department of Industrial
Engineering, Beijing, China, huangsimin@mail.tsinghua.edu.cn
1 - Considering the Effect of Outside Options in the Capacity Planning
for Hydrogen Fueling Station
Ruwen Qin, Assistant Professor, Missouri University of Science and
Technology, Department of Engineering Management, Rolla, United
States of America, qinr@mst.edu, Scott Grasman, Kevin Martin
We model and analyze the effect of an outside option in determining the optimal
capacity for hydrogen fueling stations. Through assessing the economic consequence
of the decision, this study suggests opportunities for gaining additional profits.
361
WA04
■ WA05
4 - Projections for US Flex-fuel Vehicle Structure and Renewable
Fuel Standards
Xirong Jiang, Senior consulting decision analyst, Lumina Decision
Systems, Inc, 26010 Highland Way, Los Gatos, CA, 95033, United
States of America, xirong@lumina.com, Surya Swamy, Max Henrion,
Costa Samaras
Multicriteria Decision Making
Contributed Session
Chair: Judit Lienert, Dr., Eawag: Swiss Federal Institute of Aquatic
Science and Technology, Ueberlandstrasse 133, P.O. Box 611,
Duebendorf, CH-8600, Switzerland, judit.lienert@eawag.ch
1 - A Method for Multiobjective Optimization using Trust
Region Method
Jong-hyun Ryu, Purdue University, 315 N. Grant Street, West
Lafayette, IN, 47907, United States of America, ryuj@purdue.edu,
Sujin Kim
We use ATEAM (Analytica Transportation Energy Assessment Model) to explore a
variety of scenarios to see how rapidly the US needs to adopt flex-fuel vehicles to
consume the volume of biofuels productions set by the 2010 revision of the
Renewable Fuel Standard, including high-blend E15 or E20 options.
■ WA04
We propose a method for approximating the Pareto front in a blackbox
multiobjective problem. At each iteration, each objective function on a certain
region (trust region) is approximated by a quadratic function, and a scalarization
method is applied to collect points to approximate the Pareto front. The region is
iteratively updated so as to maintain the spread of solutions. Numerical results are
presented to demonstrate the effectiveness of the proposed algorithm.
Decision Analysis II
Contributed Session
Chair: John Mamer, UCLA Anderson Grad. School of Mgmt.,
110 Westwood Plaza, D518, Los Angeles, CA, 90095-1481,
United States of America, jmamer@anderson.ucla.edu
1 - Value of Information in Spreadsheet Monte Carlo Simulation Models
Mike Middleton, Decision Toolworks, 2105 Buchanan St, San
Francisco, United States of America, Mike@DecisionToolworks.com
2 - Evolutionary Computation-based Multi-objective Approach to
Rehabilitate Interconnected Infrastructure
Avery White, Student, Texas A&M University, 3136 TAMU, College
Station, TX, United States of America, sacredfaith@tamu.edu,
Emily Zechman, Lufthansa Kanta, Alex Sprintson
For a spreadsheet planning model with uncertain inputs, value of information about
each input is useful for evaluating information-gathering efforts and for comparing
their importance. This paper describes non-macro computation methods for
spreadsheet Monte Carlo simulation, calculation of value of information for each
uncertain input, charts for presenting the results, and insights to be gained.
In the event of urban fires, cascading failures between water and electrical
distribution infrastructure systems may exacerbate municipal losses. Under-designed
water distribution systems may be further disabled through power loss. This
research takes an evolutionary computation-based approach to identify pipe
replacement strategies for urban fire scenarios to provide fire flows, maintain water
quality for normal operating conditions, and minimize pipe replacement costs.
2 - The Role of Supply Chain Structure in the Food vs. Biofuel Tradeoff
Adaora Okwo, Georgia Institute of Technology, 765 Ferst Dr.,
Atlanta, United States of America, aokwo@gatech.edu
3 - Application of Dynamic Multiobjective Programming to Supply
Chain of Crude Oil
Moses Olusola Okesola, Student, University of South Africa,
9,Solomon Okonkwo Street, Unity Estate, Egbeda, Lagos, 234,
Nigeria, okesolaj@yahoo.com
We present a micro model of the food vs biofuel tradeoff. Most macro models
informing the policy discussion fail to incorporate contracting and downstream
market power in the agricultural supply chain; both of which can significantly
influence a farmer’s decisions on which crops to supply and in which quantities. We
present a two-echelon decentralized supply chain model to illustrate the impact of
contract parameters and market power on the equilibrium supply response for food
and energy crops.
The Dynamic Multiobjective Programming (DMP) has been largely deficient in
decision problems related to integrated supply chain of crude oil in literature.We
tend to review developed methods for solving MOPP using DP technique and
identify their deficiencies.The research will focus on upstream supply chain of crude
oil in Nigeria by treating each activity along the supply chain separately with the
grand objective to optimize return function from one stage to another.
3 - Corn Ethanol Plant Investment using Real Options Analysis
Dexin Luo, Geogia Institute of Technology, 765 Ferst Drive, Atlanta,
GA, United States of America, dexin.luo@gatech.edu, Valerie Thomas
4 - Reducing Pharmaceuticals in Hospital Wastewater - MCDA Multistakeholder Elicitation Challenges
Judit Lienert, Dr., Eawag: Swiss Federal Institute of Aquatic Science
and Technology, Ueberlandstrasse 133, P.O. Box 611, Duebendorf,
CH-8600, Switzerland, judit.lienert@eawag.ch, Peter Reichert,
Nele Schuwirth
We apply real options analysis of entry-exit decision to corn ethanol plants with two
different processes: dry-milling and wet-milling. We incorporate uncertainties
regarding ethanol and corn prices and technical change. The study shows the
influence of technical change on the investment decision of individual firms with
comparison to the increase of dry-milling plants in the U.S.
4 - Dealing with the Growth of Knowledge
Norimasa Kobayashi, Assistant Professor, Tokyo Institute of
Technology, 2-12-1 Ookayama, Meguro-ku, Tokyo, 152-8552, Japan,
nkoba@valdes.titech.ac.jp
Pharmaceuticals in water bodies are of concern; they can be reduced by point
source measures. In a project with engineers, natural, and social scientists, we
studied two exemplary hospitals. We used MCDA to support the decision between
68 technological and organizational alternatives to reduce medicals. We elicited
preferences from 26 stakeholders. Our elicitation procedure reduces the time
demand, but remains methodologically satisfactory. We present elicitation challenges
and main results.
Binmore (2009) criticizes that our real decision environments are so essentially
“large” that the complete state space assumption of Bayesianism does not hold. I
model the growth of knowledge formalizing Popper (1935), and discuss how well
the decision on incomplete decision analytic models perform in different
circumstances. Particularly, I discuss that in non-cooperative games, incomplete
mental models may result both in inefficiency and efficiency.
5 - Fire Sales and Search
John Mamer, UCLA Anderson Grad. School of Mgmt., 110
Westwood Plaza, D518, Los Angeles, CA, 90095-1481, United States
of America, jmamer@anderson.ucla.edu, Steven Lippman
We study a model of asset sales via search with semi-rational buyers. A seller has a
finite (or infinite) number of items to sell, independent buyers arrive according to a
Poisson process. Each potential buyer knows the price of the last sale, and offers the
minimum of his reservation value and the price of the last sale. As a result, the
seller faces a falling offer distribution, each sales price setting the maximum offer for
subsequent sales.
362
■ WA06
WA08
5 - Case Pack Configuration and Procurement Planning
Shuang Chen, PhD candidate, University of Florida, 285 Corry
Village Apt 13, Gainesville, United States of America, scljj@ufl.edu,
Joseph Geunes
C - Ballroom E, Level 4
Tutorial: New Developments for Solving Real World
Optimization Problems by Marrying Simulation
and Optimization
We consider a retail planning problem where retailers must order in case packs
containing multiple individual products. We simultaneously consider case pack
configuration and procurement decisions. We first solve this quadratically
constrained quadratic program with integer variables using an exact linear method.
Then we propose an integrated approach combining module design and lot sizing
decisions, as well as an iterative heuristic. Our approaches perform very well
compared to solver Baron.
Cluster: Tutorials
Invited Session
Chair: Fred Glover, CTO, OpTek Systems, Inc., 1919 Seventh Street,
Boulder, CO, 80302, United States of America, glover@opttek.com
1 - New Developments for Solving Real World Optimization Problems
by Marrying Simulation and Optimization
Manuel Laguna, Professor, University of Colorado at Boulder,
419 UCB, Boulder, CO, 80309, United States of America,
laguna@colorado.edu, Jay April, Marco Better
■ WA08
C - Room 11A, Level 4
Joint Session Location Analysis/ MIF: Public-Sector
Facility Location
Companies invest billions of dollars each year in applications that can be handled by
combining simulation and optimization. These notably include problems that
involve uncertainty and complex nonlinearities, as in the areas of capital
investment, workforce composition and management, energy resource and
transmission planning, health care systems, financial portfolio optimization,
production and inventory systems, security and emergency response planning. We
identify latest advances and applications in these areas from combining simulation
and optimization, together with opportunities for future applications.
Sponsor: Location Analysis/ Minority Issues
Sponsored Session
Chair: Michael Johnson, Associate Professor, University of Massachusetts
Boston, Department of Public Policy/Public Affairs, 100 Morrissey Blvd.,
Boston, MA, 02125-3393, United States of America,
michael.johnson@umb.edu
1 - A Multi Objective Available Coverage Model
Hari Rajagopalan, Assistant Professor, Francis Marion University,
School of Business, P.O. Box 100547, Florence, SC, 29501,
United States of America, hrajagopalan@fmarion.edu, Cem Saydam,
Elizabeth Sharer, Kay Lawrimore
■ WA07
C - Ballroom F & G, Level 4
Supply Chain Optimization I
Demand for ambulances fluctuates spatially and temporally. Recent advances in
computing and spatial data have enabled EMS managers to practice dynamic
redeployment plans. In this paper we address the issue of redeployment by explicitly
considering the number of redeployment trips to be made while meeting the
coverage requirements with nearly minimal fleet size and develop fast heuristics.
We present computational statistics using real data from Charlotte, NC.
Contributed Session
Chair: Shuang Chen, PhD Candidate, University of Florida, 285 Corry
Village Apt 13, Gainesville, United States of America, scljj@ufl.edu
1 - A News-Vendor Model With External Fund Availability
Benjamin Melamed, Professor, Rutgers Business School - Newark
and New Brunswick, 94 Rockafeller Rd., Piscataway, 08554,
United States of America, melamed@rbs.rutgers.edu, Junmin Shi,
Michael N. Katehakis, Ben Sopranzetti
2 - Equity Across Groups in Facility Location
Tammy Drezner, Professor, California State University, Fullerton, 800
State College Blvd., Fullerton, CA, 92834, United States of America,
tdrezner@Exchange.fullerton.edu, Zvi Drezner
The classical news-vendor (NV) problem is to find the optimal order quantity which
maximizes the expected profit in a probabilistic demand framework. In this talk we
present studies when there is external funding available. We treat the corresponding
optimization problem as a capital-asset portfolio problem, and obtain the optimal
ordering strategy. In addition, some risk issues, such as bankruptcy risk, have are
discussed.
An equity model between groups of demand points is proposed. The set of demand
points is divided into two or more groups. For example, rich neighborhoods and
poor neighborhoods, urban and rural neighborhoods. We wish to provide equal
service to the different groups by minimizing the deviation from equality among
groups. The objective function, to be minimized, is the sum of squares of differences
between all pairs of service distances between demand points in different groups.
2 - A Model for Planning and Operating the Norwegian Seafood
Value Chain
Peter Schütz, SINTEF Applied Economics, S.P. Andersens vei 5,
Trondheim, Norway, peter.schutz@sintef.no, Kristin Uggen,
Kjetil Midthun
3 - Solving a Multi-Period School Location Problem with Capacity
Constrains using Tabu Search
Eric Delmelle, Assistant Professor, University of North Carolina at
Charlotte, Department of Geography and Earth Scienc, Charlotte,
NC, 28223, United States of America, Eric.Delmelle@uncc.edu,
Jean-Claude Thill
We discuss a model for planning the slaughtering and processing of farmed salmon.
The model also includes the operations of the well boats, such as loading conditions
at the cages and cleaning before assigning them to new regions. The problem is
subject to uncertainty, as the number of fish in a cage, their weight and size can
only be estimated, but is unknown until the fish is slaughtered.
In rapidly expanding areas, it may be necessary to build additional schools to meet
anticipated demand. A tabu search algorithm is used to solve a multi-period
capacitated p-median model, applied to a a school network location problem. The
model is flexible as it allows facility closure.
3 - The Optimum Base-Stock Levels in a Two-Echelon Supply Chain
with Service Level Constraints
Yat-wah Wan, National Dong Hwa University, Institute of Logistics
Management, Shou-Feng, Hualien, 974, Taiwan - ROC,
ywan@mail.ndhu.edu.tw, Tsung-Shung Chang
4 - Foreclosed Housing Selection using Multi-Criteria Decision Models
Michael Johnson, Associate Professor, University of Massachusetts
Boston, Department of Public Policy/Public Affairs, 100 Morrissey
Blvd., Boston, MA, 02125-3393, United States of America,
michael.johnson@umb.edu, David Turcotte, Rachel Drew
In a two-echelon supply chain of non-zero replenishment lead times, retailers adopt
base-stock policies and set minimum service levels. The objective is to find globally
optimal base-stock inventory levels of the whole chain. Such levels are found from
(i) the sample-path monotone properties of ordered quantities and of inventories on
hand with respective to base-stock levels, and (ii) in some cases, the local optima of
the objective function are decreasing with respect to base-stock levels.
Acquisition of foreclosed housing for redevelopment is a key element of U.S.
housing policy. This task requires balancing multiple criteria and assessing decisionmaker preferences, which can be difficult to quantify. We describe a multi-criteria
decision model for acquisition of real-estate-owned foreclosed housing in which we
adapt methods from stochastic processes, urban economics and facility location to
rank candidates for acquisition by a community-based organization.
4 - Optimizing the Kenya Coffee Supply Chain
Rose Karimi, Rutgers University, 1 Washington Park, Newark, NJ,
07102, United States of America, kiwanuka@pegasus.rutgers.edu,
Yao Zhao
We compare the profitability of two models: the inventory control model and the
selling-through model.In the first model based on current price information, a
decision is made to either sell all or a portion of the coffee, or to hold the coffee in
expectation of a more favorable price in the future while in the second model all
coffee is sold.
363
WA09
■ WA09
3 - Horizontal Alliances and Mergers in Multitier Supply Chains
Soo-Haeng Cho, Assistant Professor, Tepper School of Business,
Carnegie Mellon University, 5000 Forbes Ave, Pittsburgh, PA, 15215,
United States of America, soohaeng@andrew.cmu.edu
C - Room 11B, Level 4
Empirical Studies in Operations Management
Supply chains often consist of multiple tiers in each of which one or more firms
compete. Firms that belong to the same tier often form alliances or merge together.
The primary objective of such alliances or mergers is to reduce marginal costs
through economies of scale in R&D and production. In this paper, we examine the
effect of the cost-reducing alliances and mergers in one tier on non-participating
firms in the same tier and on firms in the upstream or downstream tiers.
Sponsor: Manufacturing and Service Operations Management
Sponsored Session
Chair: Serguei Netessine, Professor, INSEAD, Boulevard de Constance,
Fontainebleau, 77305, France, serguei.netessine@insead.edu
1 - Global Sourcing and Operational Performance
Karan Girotra, INSEAD, Boulevard De Constance, Fontainebleau,
France, Karan.GIROTRA@insead.edu, Marcelo Olivares
4 - Coordinating Capacity Investments in Joint Ventures
Philippe Chevalier, Professor, CORE, Université catholique de
Louvain, Voie du Roman Pays 34, Louvain-la-Neuve, 1348, Belgium,
Philippe.Chevalier@uclouvain.be, Guillaume Roels, Ying Wei
This study aims to provide the first large-scale empirical estimates on the
consequences of global sourcing on firm-level inventory performance. We compile a
novel data-set by merging data from US customs manifests and public data on firmlevel inventory performance. We estimate the impact of imports on inventory
performance and the benefit of oft prescribed operational strategies: importing
intermediate products (postponement) and importing low variability products.
We model a strategic alliance between several manufacturing firms that decide to
pool their resources so as to hedge their profits against demand variability. We
propose a type of contract that coordinates capacity investments and compare this
contract with several other contracts proposed in the literature.
2 - The Inventory Billboard Effect
Gerard Cachon, The Wharton School, 3730 Walnut St., JMHH Suite
500, Philadelphia, PA, 19104, United States of America,
cachon@wharton.upenn.edu, Santiago Gallino, Marcelo Olivares
■ WA11
The challenges associated with identifying an inventory billboard effect are
discussed. Then, using detailed data from car dealerships, we measure the extent
that inventory drives sales.
Finance/Operations Link: Flow Models
Sponsored Session
3 - Organizational Structure, Trust and Sourcing
Anupam Agrawal, University of Illinois at Urbana-Champaign,
Wohlers Hall, Champaign, IL, 61820, United States of America,
anupam@illinois.edu
Chair: Nico Vandaele, Professor, Katholieke Universiteiet Leuven,
Naamsestraat 69, Leuven, Belgium, Nico.Vandaele@econ.kuleuven.be
1 - A Newsvendor Perspective on Value-based Performance and
Risk Management
Gerd Hahn, Catholic University of Eichstaett-Ingolstadt, Auf der
Schanz 49, Ingolstadt, 85049, Germany, gerd.hahn@kuei.de,
Heinrich Kuhn
This paper focuses on the linkages between the organizational structure of a buying
firm, its relationships with its suppliers, and the resultant incoming quality of
components - how do these change dynamically? The research is based on ongoing
practices at a leading automobile manufacturer. The sourcing related organizational
arrangements are different in the car and truck making units of this firm, and lead
to different results on the above two dimensions (quality and relationships).
Economic Value Added (EVA) as a prevalent indicator of shareholder value creation
is applied to the well-known newsvendor or cost-volume-profit model. An
integrated approach to performance and risk management is developed exploiting
properties of the EVA concept. We provide a managerial framework for decisionmaking considering the risk preference of the newsvendor. A numerical example is
utilized to highlight implications of the presented approach.
4 - An Empirical Analysis of Service-based Strategies in the Automotive
Industry: The Role of Warranties
Serguei Netessine, Professor, INSEAD, Boulevard de Constance,
Fontainebleau, 77305, France, serguei.netessine@insead.edu,
Morris Cohen, Jose Guajardo
2 - Working Capital Decisions in Supply Chains Under Consideration of
Cost of Capital Rates
Erik Hofmann, Senior Lecturer, University of St. Gallen,
Dufourstrasse 40a, LOG-HSG, St. Gallen, 9000, Switzerland,
erik.hofmann@unisg.ch
We empirically analyze the role of warranties as part of the competitive strategy of
car manufacturers, using data from the US automotive industry. Challenges in
estimation, as well as implications for firms and consumers are discussed.
■ WA10
In this paper, working capital decisions are extended to supply chains, due to the
deficiencies resulting from a single-company perspective. The weighted cash
conversion cycle (WCCC) is combined with the weighted average cost of capital
(WACC) model. The amount of funds in an inter-organizational setting is
considered, transforming the WACC from an exogenous into an endogenous
decision figure. A numerical study illustrates several performance impacts on supply
chain companies.
Operations Economics
Sponsored Session
3 - Linking Operations and Finances: The Stochastic Lot
Sizing Problem
Lien Perdu, Katholieke Universiteit Leuven, Naamsestraat 69,
Leuven, 3000, Belgium, lien.perdu@kuleuven-kortrijk.be,
Nico Vandaele
Chair: Fuqiang Zhang, Washington State University in St. Louis, One
Brookings Drive, St. Louis, MO, 63130, United States of America,
fzhang22@wustl.edu
1 - Competition and the Value of Additional Replenishment Opportunity
Yen-Ting Lin, University of North Carolina, Kenan-Flagler Business
School, Chapel Hill, NC, United States of America,
Yen-Ting_Lin@unc.edu, Ali Parlakturk
In contrast with a traditional cost model, we integrate a financial flow dimension in
the stochastic lot sizing problem. The original model was built to optimize lead times
and whereas the new objective function is based on the Economic Value Added
concept, which allows a broader applicability.
We consider a manufacturer serving two competing retailers who sell their products
during a selling season. The retailers place a regular order before the selling season
begins. In addition, quick response allows a retailer to place a second order after
better demand is obtained. We examine the value of this additional ordering
opportunity for the retailers, manufacturer as well as the whole supply chain.
4 - Analysis of Card Based Flow Control in a Make-to-Order
Production Shop
Steven Harrod, Assistant Professor, University of Dayton, 1143
Ashburton Dr, Dayton, OH, 45459, United States of America,
steven.harrod@udayton.edu, John Kanet
2 - Dynamic Price and Lead Time Quotation for MTO Systems with
Contract Customers and Spot Purchasers
Baykal Hafizoglu, Arizona State University, Industrial Engineering,
SCIDSE, 699 S. Mill Ave., #501, Tempe, AZ, 85281, United States of
America, baykal@asu.edu, Esma Gel, Pinar Keskinocak
We examine the performance of a make-to-order production shop when a “pull”
regimen (Kanban, Conwip, or POLCA) is enforced. After simulating random job
routings, we conclude that flow control approaches do in fact reduce the number of
jobs in process but total system inventory (including ready jobs) increases. Further
we find that selection of priority rule has a greater influence on shop WIP than
selection of a particular card based flow control system.
We consider dynamic price and lead time quotation for a MTO company with
demand from contract customers and spot purchasers. Contract customers are
offered a uniform price and lead time, and prioritized service. Spot purchasers are
subject to dynamically quoted price and lead times, which they accept or reject with
known probability. We discuss the potential of dynamic quotation, various
properties of optimal control policies and the optimal mix of contract customers and
spot purchasers.
364
■ WA12
WA14
2 - Delaying the Delay Announcements
Achal Bassamboo, Northwestern University,
2001 Sheridan Road, Evanston, IL, United States of America,
a-bassamboo@kellogg.northwestern.edu, Gad Allon
Tactical and Operational Issues in Supply
Chain Management
This paper studies the impact of postponement of delay announcement on the
ability of the firm to communicate non-verifiable congestion information to its
customers as well as on the profits and utilities for the firm and the customers
respectively. We show that this postponement can help the firm create credibility
and augment the equilibrium language. However, in other settings this delay can
also detract the equilibrium language.
Sponsor: Manufacturing and Service Operations Management/
Supply Chain
Sponsored Session
Chair: Sila Cetinkaya, Professor, Texas A&M University, Industrial and
Systems Engineering, College Station, TX, United States of America,
sila@tamu.edu
3 - An Auction Mechanism for Optimal Procurement From Multiple
Suppliers with Asymmetric Information
Yimin Yu, Assistant Professor, City University of Hong Kong, Hong
Kong, yiminyu@cityu.edu.hk, Saif Benjaafar
Co-Chair: James Lavin, NC State University, 1321 Crab Orchard Dr #002,
Raleigh, 27606, United States of America, jalavin@ncsu.edu
1 - Uniform vs Retailer-Specific Pricing in a Supply Chain
Asoo Vakharia, Professor, University of Florida, Department of ISOM,
Gainesville, FL, 32611-7169, United States of America,
asoo.vakharia@warrington.ufl.edu, Lan Wang
We study a retailer offering a procurement contract through a sealed auction to
multiple suppliers. The production cost and the capacity of each supplier are private
information. We design a modified VCG type auction to achieve the first best such
that it is a dominant strategy for each supplier to reveal its true information.
Furthermore, this auction has the following appealing properties: (1)Individual
rational; (2)No free riding; (3)Budget balanced; (4)Coalition proof for the retailer.
Should a supplier adopt a uniform or a retailer-specific price when selling a product
to retailers with differing capabilities? Would the choice between these pricing
strategies be moderated by the competitive market structure? Insights into this
problem are provided for the cases of deterministic and stochastic end-product
demand.
4 - Strategic Diagnosis and Pricing in Expert Services
Mehmet Fazil Pac, PhD Candidate, Wharton School of Business,
University of Pennsylvania, 3730 Walnut Street, Jon M. Huntsman
Hall, Office 527.6, Philadelphia, PA, 19104, United States of America,
mpac@wharton.upenn.edu, Senthil Veeraraghavan
2 - An Order-up-to-level (OUL) Inventory Model with Stochastic
Demand and Lead Times
Daniel Silva, OR Sr. Analyst, Kimberly Clark, Latin American
Operations, KR 11A no 94 - 45, Piso 5, Bogota, Colombia,
daniel.f.silvaizquierdo@kcc.com, Germàn Riaño
Customers often cannot identify the type of service they need, therefore they rely
on experts, who also sell the service, for the diagnosis of their problem. The
information asymmetry arising upon diagnosis leads to inefficiencies in the
provision of the service. The expert has an incentive to over-provide or to ration
services, based on the demand, capacity and the waiting cost. We investigate
diagnosis, pricing and queue joining decisions in expert service markets using a
queuing framework.
We extend a periodic review, stochastic demand model to include stochastic lead
times. We assume Normally distributed lead-time demand and solve for expected
fill-rate, we achieve a better approximation than traditional methods. There is no
closed form solution for the optimal OUL, but the fill rate function is convex and we
use iterative methods to solve. Simulation results confirm fill rate goals are met by
our model, while traditional models over-shoot. Real data results will be presented.
■ WA14
3 - Stochastic Perturbed Demand Inventory Model
James Lavin, NC State University, 1321 Crab Orchard Dr #002,
Raleigh, 27606, United States of America, jalavin@ncsu.edu,
Anita Vila-Parrish, Russell King
C - Room 14, Level 4
Supply Chain Management VIII
Contributed Session
Stockouts cause customers to lose faith in a retailer and potentially turn elsewhere
to meet their future demands. Most inventory models use a penalty cost when a
stockout occurs. An alternative first proposed by Schwartz (1966) instead discounts
expected demand when stockouts occur through use of a “disappointment factor.”
We extend Schwartz’s model for the case with stochastic demand.
Chair: Wanxi Li, University of Wisconsin Milwaukee, 3202 N. Maryland
Ave., Milwaukee, WI, 53201, United States of America,
wanxili@uwm.edu
1 - The Influence of Psychological Contract Violation on Supply Chain
Decision-Making Behaviors
Stephanie Eckerd, Ohio State University, 4943 Common Market
Place, Dublin, United States of America, eckerd.2@osu.edu
4 - A Supply-side Rationale for a Firm to Bundle
Qingning Cao, PhD Candidate, University of Texas at Dallas, 800
West Campbell Road, Richardson, TX, 75080-3021, United States of
America, qxc071000@utdallas.edu, Jun Hang, Kathryn Stecke
Conflict is an inevitable phenomenon in buyer-supplier relationships. In the face of
varying types of conflict, individuals may respond differently depending on the level
of psychological contract violation experienced. We report the results of a behavioral
experiment that determines how those in boundary-spanning roles respond to
conflict in the supply chain, specifically evaluating their economic decisions before
and after an occurrence of conflict.
This paper examines a retailer’s two-product bundling decision when the supply of
one product is limited. This paper derives the retailer’s optimal prices, stocking
levels, and profits under unbundling and bundling. Demonstrating that limited
supply can induce the retailer to bundle, this paper highlights a new supply-side
rationale for bundling.
2 - Procurement and Pricing in a Decentralized Multi-tier
Assembly System
Wanxi Li, University of Wisconsin Milwaukee, 3202 N. Maryland
Ave., Milwaukee, WI, 53201, United States of America,
wanxili@uwm.edu, Xiang Fang
■ WA13
In a decentralized multi-tier assembly system, an assembler needs sets of modules
produced by different module sub-assemblers, and each module needs multiple
components purchased from different suppliers. The assembler faces stochastic
demand. We characterize the equilibrium order quantity and pricing decisions,
based on which we provide insights on the design of such multi-tier assembly
systems.
Incentives in Service Operations
Service Management Special Interest Group
Sponsored Session
Chair: Nitin Bakshi, Assistant Professor, London Business School, Sussex
Place, London, NW1 4SA, United Kingdom, nbakshi@london.edu
Co-Chair: Sang-Hyun Kim, Assistant Professor, Yale University, 135
Prospect Street, New Haven, CT, 06520-8200, United States of America,
sang.kim@yale.edu
1 - Optimal Preventive Maintenance Under Contracting
Sang-Hyun Kim, Assistant Professor, Yale University, 135 Prospect
Street, New Haven, CT, 06520-8200, United States of America,
sang.kim@yale.edu
We investigate how various maintenance service contracts impact the optimal
structure and performance of well-known preventive maintenance policies, such as
age replacement and block replacement policies. We focus on comparing the results
with those found in the classical reliability theory literature.
365
WA15
■ WA15
2 - Forecasting Stochastic Lead Times
Jack Hayya, Professor Emeritus, Penn State University, School of
Business, University Park, 16802, United States of America,
jch@psu.edu, Uttarayan Bagchi
Continuous Optimization
Consider the case of iid lead times, which theoretically cannot be predicted.
However, these lead times are subject to order crossover which transforms the iid
lead times to an AR(1) process. But this AR(1) process contains outliers which make
the residuals nonnormal. So we fit an ARCH(1) model with t-residuals.
Contributed Session
Chair: John Carlsson, Assistant Professor, University of Minnesota, 111
Church St SE, 130C, Minneapolis, MN, 55455, United States of America,
jgc@me.umn.edu
1 - The Scalar Equivalence of Optimization Criteria
Surachai Charoensri, University of Texas at Arlington, Arlington, TX,
76019, United States of America, surachai.charoensri@mavs.uta.edu,
H. W. Corley
3 - Virtual Manufacturing at Ford Motor Company
Paul E “Gene” Coffman, Jr, Technical Leader, Ford Motor Company,
6100 Mercury Drive, Dearborn, MI, 48126-2746, United States of
America, gcoffman@ford.com
Eight years ago, Ford launched a Virtual Manufacturing Center and initiated a
strategy to significantly reduce launch concerns by verifying new vehicles virtually
before physical prototypes are built and by simulating manufacturing operations
early in a new vehicle program. Ford’s recent success in customer satisfaction
surveys is due in part to the 80% reduction in launch concerns achieved to date.
We will describe the key elements of the strategy and the tools used to achieve
these results.
We show that existing optimization criteria are equivalent to the maximization of a
real-valued function in a one-dimensional Euclidean space. All and only solutions to
an optimization problem in the original criterion can be obtained by scalarization
without the typical convexity/concavity assumptions on the original objective
functions. Examples include minimax, Pareto, and set-valued optimization, as well
as cone-ordered optimization in abstract spaces.
2 - Computational Studies of Randomized Multidimensional
Assignment Problems
Mohammad Mirghorbani, The University of Iowa, 208 Engineering
Research Facility, 330 S. Madison Street, Iowa City, IA, 52240,
United States of America, smirghor@engineering.uiowa.edu,
Paul Krokhmal
■ WA17
OR For Infrastructure Development in India
We propose a new heuristic approach for solving randomized multidimensional
assignment problems (MAPs) with linear sum or bottleneck objectives that is based
on recently obtained asymptotical properties of optimal value of random MAPs. The
approach allows for drastic reduction of search space while guaranteeing high
quality of the solution, and transforms the original problem into a maximum clique
problem in multipartite graphs.
Cluster: OR/MS in India
Invited Session
Chair: Ashok Mittal, Professor, IIT Kanpur, IME Dept., IIT Kanpur,
Kanpur, UP, 208016, India, mittal@iitk.ac.in
1 - Modeling Complex Aerospace Supply Chain With Delivery
Guarantees
Dinesh Kumar, Professor, Indian Institute of Management Bangalore,
Bannerghatta Road, Bangalore, Ka, 560076, India,
dineshk@iimb.ernet.in
3 - Convex Relaxations for Cubic Polynomial Problems
Helder Inacio, Student, Georgia Institute of Technology, Georgia
Institute of Technology, Atlanta, GA, 30332, United States of
America, hinacio@isye.gatech.edu, Shabbir Ahmed, Matthew Realff
Aerospace has one of the complex supply chains that deals with assembly of
millions of parts sourced from multiple vendors across the globe. Aircraft
manufacturers expect their suppliers to deliver the parts just in time at their
manufacturing facilities. In this paper we have used queueing models to analyse an
assembly type manufacturing system with an objective to maximize the probability
of on-time delivery of the parts.
We study convex relaxations for problems with polynomial constraints with degree
less than or equal to 3. Specifically for terms of the form x^2 y we derive convex
nonlinear underestimators in a similar fashion to McCormick underestimators for
bilinear terms. We compare these estimators with other convex underestimators.
4 - A Non-convex Geometric Partitioning Algorithm for
Multi-vehicle Routing
John Carlsson, Assistant Professor, University of Minnesota,
111 Church St SE, 130C, Minneapolis, MN, 55455,
United States of America, jgc@me.umn.edu
2 - Optimal Route Selection in a Computer Integrated Raw Material
Handling Complex of an Integrated Steel Plant
Salil K Dutta, SAIL- Durgapur Steel Plant India, TQM Deptt,
Durgapur, 713203, India, salil_kumar_dutta@yahoo.co.in
We consider a stochastic vehicle routing problem in which vehicle depot locations
are fixed and client locations in a service region are unknown, but are assumed to
be i.i.d. samples from a given probability density function. We present an algorithm
for partitioning the service region into sub-regions so as to minimize the maximum
workload of any vehicle when the service region is simply connected and point-topoint distances follow some “natural” metric, such as any L^{p} norm.
For efficient operation of Raw Materials Handling Complex of an Integrated Steel
Plant, a PC based System is conceptualized. Two interactive modules: i) Optimal
Blend-mix Module based on a mathematical programming model ii) Route Selection
and Prioritization Module based on a integer programming model in conjunction
with a Heuristic, has been proposed.
3 - Understanding Passanger Switching Behavior and Yield
Management for Indian Railways
Ashok Mittal, Professor, IIT Kanpur, IME Deptt, IIT Kanpur, Kanpur,
UP, 208016, India, mittal@iitk.ac.in, Rahul Sharma
■ WA16
Indian rail provides different type of accomodation to rail passangers. For most of
the trains seats in the choice class are not available until booked well in advance.
We model the switching behavior of the passanges classified in different need
categories. We use this behaviour to model yield management for Indian railways.
Manufacturing II
Contributed Session
Chair: Paul E “Gene” Coffman, Jr, Technical Leader, Ford Motor
Company, 6100 Mercury Drive, Dearborn, MI, 48126-2746,
United States of America, gcoffman@ford.com
1 - Optimization of Stochastic Flow Lines using Exact Linear
Programming Formulations
Raik Stolletz, Associate Professor, Technical University of Denmark,
Department of Management Engineering, Lyngby, Denmark,
raist@man.dtu.dk
Several sampling approaches have been proposed to analyze stochastic flow lines
with finite buffer capacities. If the number of buffers is given, the performance can
be evaluated via a Linear Programming formulation. This presentation shows
linearization approaches if the number of buffers is a decision variable. We develop
a two-step optimization approach, where a discrete time approximation is used to
get a first solution to speed up the solution of the exact linearization.
366
■ WA18
WA21
3 - Distributionally Robust Pricing and Replenishment Decisions for
Multiple Products
Dan Iancu, IBM T.J. Watson Research Center, P.O. Box 218,
Yorktown Heights, NY, 10598, United States of America,
dan.iancu@us.ibm.com
OR in Practice I
Sponsor: CPMS, The Practice Section
Sponsored Session
In the current presentation, we discuss formulations and computational aspects
related to determining pricing and replenishment policies for multiple products
under uncertain customer demand. In particular, we look for policies directly
parameterized in the model disturbances. Preliminary computational results, based
on both synthetic, as well as real data from a large US retailer, are very promising,
with adjustable policies considerably improving over open-loop decisions.
Chair: Laura Galli, DEIS University of Bologna, Viale Risorgimento, 2,
Bologna, 40136, Italy, l.galli@unibo.it
Co-Chair: Bjarni Kristjansson, President, Maximal Software, Inc., 933 N.
Kenmore St., Suite 218, Arlington, VA, 22201, United States of America,
bjarni@maximalsoftware.com
1 - OR at Ford
Erica Klampfl, Technical Leader, Ford Research & Advanced
Engineering, RIC Building, MD 2122, 2101 Village Rd, Dearborn, MI,
48124, United States of America, eklampfl@ford.com
■ WA20
Challenges and Perspectives in Price
Demand Relationship
I will provide a sampling of OR problems in areas such as Sustainability,
Manufacturing, Purchasing, Product Development, Marketing, and Finance. We
apply an analytical approach to understand the environmental implications of our
products, enhance the sustainability of our business, and provide sound scientific
input for corporate strategy and regulatory interactions.
Sponsor: Revenue Management and Pricing Section
Sponsored Session
Chair: Aihong Wen, PROS Holdings, Inc., 3100 Main St Suite 900,
Houston, TX, 77002, United States of America, awen@prospricing.com
1 - Using Forecasts of Competitor Prices to Increase Sales
Evan Brott, Scientist, PROS, 3100 Main Street #900, Houston, TX,
77025, United States of America, EBROTT@prosrm.com
2 - Robust Planning and Online Re-scheduling for the Train
Routing Problem
Laura Galli, DEIS University of Bologna, Viale Risorgimento, 2,
Bologna, 40136, Italy, l.galli@unibo.it, Alberto Caprara, Leo Kroon,
Gabor Maroti, Paolo Toth
Accurate predictions of competitor prices are invaluable for developing pricing
strategies. By analyzing market conditions and recent pricing actions, we show a
method of calculating an array of expected future competitor prices. Businesses may
utilize this array to position themselves at a preferred position relative to a major
competitor. Additionally, we show how the array can be used as input into rankbased optimization, to maximize margins subject to the expected competitive
landscape.
Train Routing is a problem that arises in the early phase of the passenger railway
planning process. However, train delays often disrupt the routing schedules thus
railway nodes are responsible for a large part of the delay propagation. In this paper,
we propose robust models and re-scheduling algorithms for train routing, and
design a simulation framework to evaluate and compare their effectiveness. We
present computational results based on real-world data from the Italian railways.
3 - Combinatorial Model for Crew Scheduling in Train Transportation
Hector Ramirez Cabrera, CMM, Universidad de Chile, Avda. Blanco
Encalada 2120, Santiago, Chile, hramirez@dim.uchile.cl, Jorge
Amaya, Paula Uribe
2 - A General Framework for using Customer Sensitivity to Execute
Pricing Strategies
Ed Gonzalez, Associate Scientist, PROS, 3100 Main St, Suite 900,
Houston, TX, 77002, United States of America,
EGonzalez@prosrm.com
This crew scheduling problem can be expressed as follows: given a set of crew teams
(a pair composed by a driver and an assistant) and a set of trips (travel from one
station to another one), the aim is to find an optimal allocation of these crews to
the given trips satisfying operational constraints, such as labor laws, specific contract
conditions, among others. The objective of our problem is to equilibrate the number
of working hours realized by each crew in a given period of time.
In this presentation, we demonstrate a general framework which allows for the
automation of pricing strategies based on both business rules and fiscal goals. The
main components of this framework are (1) developing price sensitivity (2)
optimizing over given constraints and (3) measuring the effects of a pricing strategy
at both the macro and micro level.
3 - Data Mining Techniques in Modeling Price Elasticity
Aihong Wen, PROS Holdings, Inc., 3100 Main St Suite 900, Houston,
TX, 77002, United States of America, awen@prospricing.com
■ WA19
Modeling price elasticity has always been a key step in pricing optimization. This
presentation discusses the motivation behind seeking data mining tools for this
challenging task, as well as our proposals and case study.
Computational and Robust Approaches to Inventory
and Revenue Management
Sponsored Session
■ WA21
Chair: Dan Iancu, IBM T.J. Watson Research Center, P.O. Box 218,
Yorktown Heights, NY, 10598, United States of America,
dan.iancu@us.ibm.com
1 - A Dynamic Near-optimal Algorithm for Online Linear Program with
Application to Revenue Management
Zizhuo Wang, Stanford University, 14 Comstock Cir, Apt 106,
Stanford, United States of America, zzwang@stanford.edu, Yinyu Ye,
Shipra Agrawal
Carbon Reduction Policy Analysis
Sponsor: Service Science
Sponsored Session
Chair: Brian Jacobs, Assistant Professor, Michigan State University,
Supply Chain Mgt Dept, N349 North Business Complex, East Lansing,
MI, 48824-1122, United States of America, jacobsb@bus.msu.edu
1 - Investment Planning for Electricity Generation Expansion Under
CO2 Emission Reduction Policies
Dong Gu Choi, Georgia Institute of Technology, 765 Ferst Drive, NW,
Atlanta, GA, 30332, United States of America,
doonggus@gatech.edu, Valerie Thomas
We study a network revenue management problem where the customers come
sequentially and decisions are made online. Our approach is distribution-free. We
only assume that the customers come in a random order. By using a dynamic
pricing algorithm where the prices come from the solution of a series of linear
program, our algorithm is near-optimal given the initial inventory is large enough.
This algorithm can be applied to a wide range of revenue management and resource
allocation problems.
As electricity demand increases and existing power plants age, electricity generators
decide on supply technologies for new investment. This talk addresses the effects of
CO2 emission reduction policies on the investment decision of an electricity
generating firm. A dynamic programming model,incorporating policy uncertainty, is
developed for technology investment choice.
2 - A Geometric Characterization of the Power of Finite Adaptability in
Multi-stage Stochastic Optimization
Andy Sun, Massachusetts Instititute of Technology, Operations
Research Center, 50 Memorial Drive, Cambridge, MA, United States
of America, sunx@mit.edu, Vineet Goyal, Dimitris Bertsimas
We show a significant role that geometric properties of the uncertainty sets, such as
symmetry, play in determining the power of robust and finitely adaptable solutions
in multi-stage stochastic and adaptive optimization problems. We propose good
approximation solution policies with performance guarantees that depend on the
geometric properties of the uncertainty sets. To the best of our knowledge, these are
the first approximation results for the multi-stage problems in such generality.
367
WA23
■ WA24
2 - China’s Regional CO2 Emissions: Characteristics and Emission
Reduction Policies
Lei Meng, Xi’an Jiaotong University, Box 1875, No.28 Xianning West
Road, Xi’an, 710049, China, mleenig@gmail.com, Yong Xue,
Ju’e Guo
Network Models for Counterterrorism
Sponsor: Public Programs, Service and Needs
Sponsored Session
This paper analyzes the characteristics of regional CO2 emissions in China, using
province level panel data from 1997 to 2007. The results show that there’re
remarkable regional disparities among eastern coastal, midland and western areas.
In view of uneven regional development and reverse distribution of energy
resources and consumption, the CO2 emission reduction policies need customized
combination of tax, price, investment and transfer payment to meet the actual
situation in various areas.
Chair: Susan Martonosi, Assistant Professor, Harvey Mudd College,
Department of Mathematics, 301 Platt Boulevard, Claremont, CA, 91711,
United States of America, martonosi@math.hmc.edu
1 - A Network Flow Approach to Terrorist Network Disruption
Susan Martonosi, Assistant Professor, Harvey Mudd College,
Department of Mathematics, 301 Platt Boulevard, Claremont, CA,
91711, United States of America, martonosi@math.hmc.edu,
Doug Altner
3 - Shareholder Value Effects of Voluntary Emissions Reductions
Brian Jacobs, Assistant Professor, Michigan State University, Supply
Chain Mgt Dept, N349 North Business Complex, East Lansing, MI,
48824-1122, United States of America, jacobsb@bus.msu.edu
We present a new network disruption technique that tries to make otherwise
secretive members of a terrorist group more visible. Through vertex deletion, this
technique forces the secretive members to increase their participation in network
communication. This talk will illustrate our disruption metric based on network
flows, address graph-theoretic characteristics of promising vertices to target and
discuss some computational challenges.
Recent empirical evidence has demonstrated that the stock market reacts negatively
to firm announcements of voluntary emissions reductions. In this work, we study
how certain contextual factors influence the market reaction. Factors include the
type of emission (regulated or unregulated), firm and industry characteristics,
energy prices, and whether the firm’s announcement was standalone or part of a
government or NGO initiative.
2 - Diverting Communication Through a Clandestine Leader in a
Social Network
Doug Altner, Assistant Professor, United States Naval Academy,
United States of America, altner@usna.edu, Susan Martonosi
4 - Optimal Fuel Conversion Strategy of Power Plant Under Different
Carbon Policies
Xiaohua Wu, Rensselaer Polytechnic Institute, 903 Peoples Ave
Apt 3, Troy, NY, 12180, United States of America, wux4@rpi.edu,
Aparna Gupta
This talk investigates the following optimization problem: given a social network
with a key vertex and a finite budget for deleting vertices, which vertices should be
deleted to maximize the amount of communication that must be sent through the
key vertex if the amount of communication between each pair of vertices equals the
maximum flow between them? We present a meta-heuristic approach to this
problem as well as computational results.
The carbon policy will accelerate the fuel type conversion process. In this paper, a
general model of optimizing the long term fuel conversion strategy of a generator
under different carbon policies is built and analyzed. The stochastic price evolutions
of fuels, electricity and carbon emission are modeled to identify the impact of
market fluctuations. Key decision factors are optimized to achieve the generator’s
best economic performance and create a framework to assess policy impact.
3 - Tradeoffs in the Structure of Terrorist Networks
Alexander Gutfraind, Postdoctoral Fellow, Los Alamos National
Laboratory, Theoretical Division, Mail Stop B284, Los Alamos, NM,
87545, United States of America, gfriend@lanl.gov
■ WA23
Terrorist groups and other secret societies have a network structure reflecting their
objectives of survival and attack. This talk will introduce a model that quantifies
those using discrete optimization. Solving the model shows that the optimal
structure of such networks is based on cells. Open non-violent activism pays under
just two conditions: extreme tolerance and extreme repression. The model can also
be used to design vital infrastructure networks.
C - Room 18D, Level 4
Optimization in the Service Sector
Sponsored Session
4 - Counter-Radicalization Influence Campaigns and Social Networks:
What Does the Data Say?
Richard Colbaugh, Sandia National Laboratories/New Mexico Tech,
22 Camino Don Carlos South, Santa Fe, NM, 87506,
United States of America, rcolbau@sandia.gov, Kristin Glass
Chair: Ada Barlatt, Assistant Professor, University of Waterloo,
Department of Management Sciences, 200 University Avenue West,
Waterloo, ON, N2L3G1, Canada, abarlatt@uwaterloo.ca
1 - Public School’s Meal Program: Finding the Best
Cost-effective Menu
Betzabe Rodriguez, Assistant Professor, University of Puerto Rico at
Mayaguez, Call Box 9000, Mayaguez, PR, 00681, Puerto Rico,
betzabe.rodriguez@upr.edu, Magaly Gonzalez
This talk presents results of a model-based, empirically-grounded study of social
networks and influence campaigns and summarizes the practical implications of
these findings. Interestingly our investigation reveals that some conventional
wisdom regarding social networks and influence is either incomplete or incorrect.
We consider two main topics: 1.) understanding influence generation/propagation/measurement as network dynamics phenomena, and 2.) roles for social media in
influence campaigns.
Meal’s assortment highly affects the operational costs in the supply chain for the
Puerto Rico School’s Meal Program (PRSMP). The government must comply with
nutritional and service requirements while balancing delivery frequencies and
transportation costs. We have developed a mathematical formulation for the
operational costs of the food supply chain, with the objective to find a low cost
meal’s assortment for the PRSMP.
■ WA25
2 - Applying Value-at-Risk and Conditional Value-at-Risk to the
Selective Newsvendor
Arleigh Waring, University of Michigan, 1205 Beal Ave, Ann Arbor,
MI, 48109, United States of America, awaring@umich.edu
Transportation, Intelligent Systems II
Contributed Session
The selective newsvendor considers a single product firm that sells to several
different markets in a single selling season. The firm decides which markets to serve
and the total inventory to procure a priori. We evaluate the selective newsvendor
using two common risk measures: Value-at-Risk and Conditional Value-at-Risk. We
show the optimal order quantity and describe a selection criterion for the markets to
serve and then compare the inherent tradeoffs between the two methods.
Chair: Ali Guner, Research Assisstant, Wayne State University,
4815 Fourth St., Detroit, MI, 48202, United States of America,
arguner@wayne.edu
1 - A Real Time Dynamic Rideshare System
Ali Haghani, Professor, University of Maryland, College Park, 1173
Glenn L. Martin Hall, College Park, MD, 20742, United States of
America, haghani@umd.edu, Keivan Ghoseiri, Hadi Sadrsadat,
Masoud Hamedi
3 - Evaluating Tradeoffs in Implementing Alternative
Workweek Schedules
Ada Barlatt, Assistant Professor, University of Waterloo, Department
of Management Sciences, 200 University Avenue West, Waterloo,
ON, N2L3G1, Canada, abarlatt@uwaterloo.ca, Juan Vera
This paper presents an optimization model for a real-time dynamic rideshare system.
The model maximizes the overall system performance in real time subject to ride
availability, capacity, and passenger and driver time window constraints while
considering users’ preferences. Model formulation and results are presented.
Climate change, 24/7 retail outlets, and technological advances have led to changes
in the way people work. Around the globe, employees are switching to from the
traditional 9AM to 5PM schedule to alternative workweek (AWW) schedules. In this
presentation we will discuss the models developed to evaluate the tradeoffs between
the benefits (e.g., increased operating hours) and the concerns (e.g., facilitating
employee communication) in implementing AWW schedules.
368
2 - Robust Multiple Priority Traffic Signal Control with Vehicle-toInfrastructure Communication Systems
Qing He, University of Arizona, 1127 E James E. Rogers Way,
Tucson, AZ, 85721, United States of America,
heqing@email.arizona.edu, Larry Head, Jun Ding
WA27
mining techniques were used to analyze the inpatient discharge data from an urban
hospital. Four models were built to predict ALOS. Our results indicated that the
Ensemble model was the best fit and age and chronic disease were the important
predictors.
4 - Examining Relationships Between Medical Home and
Patient Experience
Sharon Johnson, Associate Professor, Worcester Polytechnic
Institute, Department of Management, 100 Institute Road,
Worcester, MA, 01566, United States of America, sharon@wpi.edu,
Edward Westrick, Lori Pelletier
This paper examines the multiple priority problems in traffic signal control under
the condition that vehicle-to-infrastructure communication is available. Given the
current multiple priority request information from on-board equipment (OBE), a
robust MILP is developed with actuated control integrated to mitigate the delay for
both vehicles with priority and passenger cars. A numerical experiment with
VISSIM and GAMS shows the effectiveness of proposed approach.
The Patient-Centered Medical Home (PCMH) is a new model for comprehensive
primary care that seeks to strengthen the physician-patient relationship. This
exploratory study utilizes Pearson correlation coefficients to examine relationships
between PPC-PCMH Survey results, which measure adoption of PCMH structures,
and patient experience data. The results show an unexpected negative correlation
between the PPC-PCMH structures of access and communication and the related
patient experience measure.
3 - Relationship of Pretrip Traveler Information System to
Non-motorized and Public Traffic in China
Yi Zhang, School of Transportation Engineering, Tongji University,
No.4800 Cao’an Road, Shanghai, China, Shanghai, China,
darrenzhy@gmail.com, Meiping Yun, Xiaoguang Yang
Traveler information system is able to change travelers’ travel behavior and alleviate
congestion. Based on a Travel Desire Survey in Zhongshan City, China, the
relationship of pretrip traveler information system to non-motorized and public
traffic was examined. The commuters’ propensity to change travel mode from
private car to non-motorized and public traffic was obtained. It is also showed that
the propensity would vary in the context of different trip distance and travelers’
characteristics.
■ WA27
Linear Programming
4 - Dynamic Routing in Stochastic Time-Dependent Networks for
Milk-Run Tours with Time Windows
Ali Guner, Research Assisstant, Wayne State University,
4815 Fourth St., Detroit, MI, 48202, United States of America,
arguner@wayne.edu, Ratna Babu Chinnam, Alper Murat
Contributed Session
Chair: Holly Floyd, Texas State University-San Marcos, 250 S. Stagecoach
Trl. #136, San Marcos, United States of America, hf1046@txstate.edu
1 - Explore the Higher-Order Rescaling Perceptron Algorithm
Dan Li, Department of Industrial and Systems Engineering,
Lehigh University, 200 West Packer Ave, Bethlehem, PA, 18015,
United States of America, dal207@lehigh.edu, Tamàs Terlaky
JIT requires frequent and reliable pick-ups and deliveries within specified time
windows. However, growing congestion on road networks is increasing variability in
travel times, making it difficult to achieve efficient and reliable deliveries. We
investigate the impact of utilizing real-time ITS information to route the vehicle.
Our dynamic routing algorithm handles milk-run tours under a TSP framework,
while modeling congestion on arcs as stochastic and time-dependent congestion
states.
The rescaling perceptron algorithm solves LO problems with high probability in
O(nln(1/r)) iterations, where r is the radius of the largest inscribed ball. It uses one
vector to rescale the system at each iteration. We realize rescaling by using parallel
processors and several vectors in one higher-order step. We explore how the
number and quality of vectors affect the rescaling rate. With properly chosen
vectors, we get better rescaling rates and improve the complexity.
■ WA26
2 - A New Method to Solve Linear Programming Problems
Oscar Buitrago, Professor, Universidad Libre de Colombia,
oscary.buitragos@unilibrebog.edu.co, osyesu@gmail.com, Bogotà
D.C, Colombia, oscary.buitragos@unilibrebog.edu.co, Andres Ramirez
Data Mining and Knowledge Discovery in Health Care
Many methods have been developed for solving LP problems, including the famous
Simplex and interior point algorithms. In this study a new procedure for solving LP
problems is described, based on orthogonal projections that move through the
polyhedron frontier which defines the feasible region until it reaches the optimal
point.
Sponsor: Data Mining
Sponsored Session
Chair: Durai Sundaramoorthi, Assistant Professor, Missouri Western State
University, 4525 Downs Drive, Saint Joseph, MO, 64507, United States of
America, dsundaramoorthi@missouriwestern.edu
1 - An Adaptive Pain Management Framework
Ching-Feng Lin, Student, UTA, 212 S Cooper St. #220, Arlington,
TX, 76013, United States of America, ching-feng.lin@mavs.uta.edu,
Victoria Chen, Robert Gatchel
3 - Optimal Deployment Plan of Emission Reduction Technologies
Muhammad Bari, Student, Texas A&M University, University Dr.,
College Station, TX, 77843, United States of America,
ehsanulbarihome@yahoo.com, Josias Zietsman, Luca Quadrifoglio,
Mohamadreza Farzaneh
The Eugene McDermott Center for Pain Management at the University of Texas
Southwestern Medical Center at Dallas conducts a two-stage interdisciplinary pain
management program that considers a wide variety of treatments. We structure this
decision-making process using dynamic programming to generate adaptive
treatment strategies for this two-stage program. State transition models were
derived using data from the two-stage pain management program.
The objective of this research was to develop methodologies for optimal deployment
of emission reduction technologies for non-road equipment in a cost effective and
optimal manner. The multi-objective problem consists of two weighted objectives,
(i) maximizing NOx reduction and (ii) maximizing fuel savings. The models
developed in this study serves as a tool to assist the decision makers to decide about
the deployment preference of technologies.
2 - The Role of Insurance Claims Databases in Healthcare Research
Yihan Guan, PhD Candidate, Stanford University, Huang Engineering
Center 212F, Stanford, CA, 94305, United States of America,
yihan@stanford.edu, Margret Bjarnadottir
4 - A Multi-Period Energy and CO2 Emission Optimization Toward
Sustainable Automotive Manufacturing
Seog-Chan Oh, Senior Researcher, General Motors R&D, 30500
Mound Road, Warren, MI, 48090, United States of America,
seog-chan.oh@gm.com, Stephan Biller
Health insurance claims data have been used in a wide spectrum of health care
research during the past two decades, including studying drug therapy outcomes,
assessing quality of care, estimating population disease burden, predicting health
care cost, and detecting adverse drug effects. This talk discusses the evolution of
applications of claims data, the current research frontier associated with claims data,
and some future opportunities.
Fluctuating energy prices and enactment of climate change legislations add
increasing uncertainty in costs associated with energy and CO2 emission for
automotive companies. To combat the challenges, we propose a mixed-integer
optimization model to maximize the reduction of energy and CO2 emission costs for
the automotive manufacturing process. Given a multi-year budget, we analyze
different scenarios, assuming different impacts of energy prices and environmental
regulations.
3 - Analyzing Patient Discharge Data From an Urban Hospital using
Data Mining Techniques
Xiuli (Shelly) Qu, Assistant Professor, North Carolina A&T State
University, 1601 E. Market Street, 424 McNair Hall, Greensboro, NC,
27411, United States of America, xqu@ncat.edu, Xiaochun Jiang,
Lauren Davis
As aging is beginning to impact the baby boom generation, they begin to experience
more chronic diseases and need more inpatient care. To deal with this trend,
hospitals need to reduce the average length of stay (ALOS). In this study, data
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WA28
■ WA28
2 - Hierarchical Simulation Modeling Framework for Electrical Power
Quality and Capacity
Esfandyar Mazhari, University of Arizona, 1127 East James E. Rogers
Way, Tucson, AZ, 85721-0020, United States of America,
emazhari@email.arizona.edu, Young-Jun Son
C - Room 4C, Level 3
Health Management of Complex Systems
Sponsor: Quality, Statistics and Reliability
Sponsored Session
A two level hierarchical simulation modeling framework is proposed for an electric
power network involving PV-based solar generators, various storage units, and grid,
where the lower level model concerns power quality and the higher level model
concerns capacity. The higher level is based on agent-based modeling while the
lower level is based on circuit-level, continuous time modeling. An integration and
coordination framework is developed, and it is demonstrated with a utility level
scenario.
Chair: Qingyu Yang, Assistant Professor, Wayne Sate University,
4815 Fourth Street, Detroit, MI, 48202, United States of America,
qyang@wayne.edu
Co-Chair: Jian Liu, Assistant Professor, University of Arizona,
Rm 268, 1127 E. James E. Rogers Way, Tucson, AZ, 85741,
United States of America, jianliu@email.arizona.edu
1 - Multi-level Multi-State Information Integration for System
Performance Prediction
Jian Liu, Assistant Professor, University of Arizona, Rm 268, 1127 E.
James E. Rogers Way, Tucson, AZ, 85741, United States of America,
jianliu@email.arizona.edu
3 - Reliability Issues in Power System Planning and Operation with
Renewable Energy Sources
Chanan Singh, Regents Professor, Texas A&M University,
Department of Electrical & Computer Engi, College Station, TX,
77843, United States of America, singh@ece.tamu.edu
Heterogeneous data available at different levels of a complex system create great
opportunity to more accurately predict the system level performance. This research
provides a Bayesian approach that simultaneously combines multi-state event data
of interdependent components and subsystems. A simulation example demonstrates
the capability of the approach.
Renewable energy sources are fast penetrating the power grid. It is estimated that
wind power alone may be close to 20 percent of the power scenario in America and
many European nations have similar targets.Such significant penetrations of
renewable energy pose considerable challenges for power system reliability in
planning and operation. This presentation will review this problem and share some
results to model and analyze the impact of their integration on reliability of the
power grid.
2 - Sensor Recovery in Multivariate Condition Monitoring Systems
Haitao Liao, Assistant Professor, The University of Tennessee, 211
Pasqua Building, Knoxville, TN, 37996, United States of America,
hliao4@utk.edu, Jian Sun
4 - Virtual Models of Wind Turbines
Andrew Kusiak, Professor, The University of Iowa, Mechanical and
Industrial Engineering, Iowa City, IA, 52242, United States of
America, andrew-kusiak@uiowa.edu
Loss of sensor readings due to malfunction of connectors and/or sensors is crucial to
fault diagnosis and prognosis in a multichannel condition monitoring system. To
improve the operational reliability of the overall system, effective sensor recovery
becomes an important, value added technique. This work addresses a statistical
sensor recovery methodology to enhance multichannel condition monitoring.
Complex nature of the wind, makes modeling wind turbines is a major challenge.
Data mining offers algorithms for modeling wind turbines. A methodology for the
development of virtual models of wind turbines is presented. The virtual models are
developed and tested with data collected at a wind farm. Several data-mining
algorithms for parameter selection and model extraction are analyzed. The research
results are illustrated with industrial case studies.
3 - Power Reliability Management in Smart Grids via Virtual
Energy Provisioning
Tongdan Jin, Texas State University, 601 University Drive, San
Marcos, TX, 78666, United States of America, tj17@txstate.edu,
Ying Yu, Mahmoud Mechehoul
■ WA30
We propose a novel demand side management concept called Online Purchase
Electricity Now (OPEN) to minimize load variations and generation uncertainties
caused by renewable energies. The OPEN system allows customers to order and
request advanced electricity via the Internet as if performing online purchasing. It
aims for customers to achieve “order exactly what they need, and consume exactly
what they ordered”. The new concept has great potentials and promises for smart
grid technologies.
Reliability III
Contributed Session
Chair: Elias Keedy, PhD Student, University of Houston, S350
Engineering Bldg 1, Houston, TX, 77204, United States of America,
eliekeedy@yahoo.com
1 - Reliability Modeling in the Design of a New Energy Concept
Sarah Riddell Powers, Lawrence Livermore Natl Lab, 7000 East
Avenue, L-153, Livermore, CA, United States of America,
powers22@llnl.gov
4 - Failure Profile Analysis of Repairable Systems
Qingyu Yang, Assistant Professor, Wayne Sate University, 4815
Fourth Street, Detroit, MI, 48202, United States of America,
qyang@wayne.edu, Yong Chen, Yili Hong, Jianjun Shi
Laser Inertial Fusion Energy (LIFE) is an advanced energy technology under
development at LLNL. Achieving high system availability is a key project goal for
the economic competitiveness of LIFE. A model is developed to simulate and study
the reliability of various system designs, maintenance strategies and optimal spare
component levels. Results show the advantage of design modularity in achieving
high system availability without needing high component reliability thus expediting
time to market.
The relative failure frequency among major failure modes of a repairable system is
referred to as failure profile. Identification of failure profile can provide valuable
information for system design and maintenance management. In this research, a
statistical model and two testing procedures are developed to study the statistical
properties of the failure profile. The efficiency of the developed methods is verified
by a case study of a high throughput screening (HTS) process.
2 - Optimal Maintenance for Linear Consecutively Connected Systems
Rui Peng, Department of Industrial and Systems Engineering,
National University of Singapore, Singapore, ISE Department, BLK
E1A, NUS, Singapore, Singapore, Singapore, g0700981@nus.edu.sg,
Gregory Levitin, Szu Hui Ng, Min Xie
■ WA29
Renewable Energy Integration Into Power Systems for
Smart Operations
This paper considers a linear multi-state consecutively connected system (LMCCS)
consisting of N+1 linear ordered elements. Each element can provide a connection
between the position in which it is allocated and the next few positions. The system
fails if the first element is not connected with the (N+1)th element. A framework is
proposed to solve the cost optimal maintenance strategy of the system subject to
reliability requirement.
Sponsored Session
Chair: Eunshin Byon, PhD, Postdoctoral Research Associate, Texas A&M
University, 241 Zachry, 3131 TAMU, College Station, TX, 77840,
United States of America, esbyun@neo.tamu.edu
1 - Impact of Environmental Factors to the Degradation of Solar
Photovoltaic Module
Rong Pan, Assistant Professor, Arizona State University, Sch Compt
Infor & Dec Sys Engr, Tempe, AZ, 85287, United States of America,
Rong.Pan@asu.edu
3 - Comparative Study of Stochastic Models to Estimate Reliability of
Infrastructure Systems
Raha Akhavan-Tabatabaei, Assistant Professor, Universidad de los
Andes, Cra 1 Este # 19A-40, Bogotà, Colombia,
r.akhavan@uniandes.edu.co, Edgar Mauricio Sànchez Silva,
Juan Sebastian Borrero
We consider the problem of infrastructure reliability subject to progressive
deterioration and shocks. We consider the deterioration mechanisms and compare
the performance of various stochastic models in describing the remaining life of a
component. Some conclusions are shown and stochastic models are classified
according to their efficiency.
To make the solar energy economically competitive, PV manufacturers typically
provide 20-30 year warranties to their customers. In this talk, we present a practical
approach to weather modeling and its usage in PV module degradation analysis. We
have analyzed the performance data of several PV modules collected over a long
time of period (approximately 15 years). These data will be used to demonstrate the
methodology to be developed in this study.
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4 - Reliability and Maintenance of Stents Based on Probabilistic
Analysis of Multiple Failure Processes
Elias Keedy, PhD Student, University of Houston, S350 Engineering
Bldg 1, Houston, TX, 77204, United States of America,
eliekeedy@yahoo.com, Qianmei Feng
■ WA32
The high demand in counteracting the effects of atherosclerosis and the ignorance of
the probabilistic aspects in existing studies make the investigation of stents reliability
a competitive concern. Based on fracture mechanisms, we analyze two processes:
delayed and instantaneous failures. General reliability and maintenance models are
developed to acquire an optimal replacement policy of stents. Our work provides
new perspectives on approaching reliability concepts in medical devices evolution.
Sponsor: Computing Society
Sponsored Session
WA33
Applications and Heuristics Methods in
Integer Programming
Chair: Haibo Wang, Assistant Professor, Texas A&M International
University, 5201 University Blvd, Laredo, TX, 78041, United States of
America, hwang@tamiu.edu
1 - An Approach for Parallel Machine Job Scheduling Problem with
Interrelated Processing Times
Bahram Alidaee, The University of Mississippi, School of Business,
University, United States of America, balidaee@bus.olemiss.edu,
Haibo Wang
■ WA31
Forecasting I
This paper addresses the parallel machine job scheduling problem with interrelated
processing times, which has applications in many areas such as storage allocation in
computer design, organization restructuring, continuous project scheduling, and
scheduling in political campaigns. we present a quadratic unconstrained binary
optimization(QUBO) model and solve it with a neighborhood search heuristic. The
computational time and the optimization gap reduction are reported.
Contributed Session
Chair: Ozden Gur Ali, Koc University, Sariyer, Istanbul, Turkey,
oali@ku.edu.tr
1 - Social Media Aided Event Forecasting
Mohammad Ali Abbasi, PhD Student, Arizona State University, 699
S. Mill Ave. #553, Attn: Mohammad Ali Abbasi, Tempe, AZ, 85281,
United States of America, ali.abasi@asu.edu
2 - Solving Large Max Cut Problems using Tabu Search
Gary Kochenberger, Professor, University of Colorado at Denver,
1250 14th Street, Denver, 80217, United States of America,
Gary.Kochenberger@ucdenver.edu, Haibo Wang, Fred Glover,
Zhipeng Lu, Jin-Kao Hao
We introduce a novel method to forecast social events and behaviors of
communities in the society. We’ve crawled tweets and blog posts of specific groups
for a period of 5 months and classify them using opinion mining methods to extract
members’ intention for specific events. Simultaneously we track the communities’
real (on the ground) activities. Experiments showed that with enough number of
online activities we can forecast the events related to the communities with high
confidence.
Large Max Cut Problems continue to pose a challenge for most approaches
presented in the literature. In this paper we report our experience with a new Tabu
Search approach for the general unconstrained binary quadratic program as it is
applied to max cut test problems. Best known results on many instances with up to
10,000 vertices are reported.
2 - Time Series Forecasting in Oracle Crystal Ball
Samik Raychaudhuri, Oracle Americas Inc., 2033 N Fork Dr,
Lafayette, CO, 80026, United States of America, samikr@gmail.com,
Eric Wainwright
3 - Warehouse Management - Cross Docking
Jun Huang, Texas A&M International University, United States of
America, huangjundragon@sina.com, Haibo Wang
In this presentation we will have an overview of the functionality provided by
Oracle Crystal Ball’s (CB) Predictor engine. CB Predictor has an intuitive interface
for selecting, managing and cleaning data, outlier detection and filling in missing
values, running multiple seasonal and nonseasonal forecasting algorithms and
regression on large datasets, and a coherent way of presenting and extracting results
or generating reports. We will also have a sneak preview of forthcoming features.
Warehouse management is a critical topic in logistic research field. The warehouse is
divided into several functional areas such as reserve storage area, order picking area
and cross docking. This study will combine the cross docking problem with storage
area layout design and products allocation by using the graph partition method as
finding a partition of the vertices of a given graph into subsets satisfying certain
properties. Thus, the aforementioned problem can be solved more properly.
3 - Using Conditional Kernel Density Estimation for Wind Power
Density Forecasting
Jooyoung Jeon, University of Oxford, 2 Alan Bullock Close,
St Clements, Oxford, United Kingdom,
joo.jeon@smithschool.ox.ac.uk, James Taylor
■ WA33
Integrating Constraint Programming and OR
Wind power is recognized as one of the most promising renewable energy resources.
Despite great benefits from wind power density forecasting, most research has
focused on point forecasting. We develop a novel approach to producing wind
power density forecasts. The inherent uncertainty in wind speed and direction and
the stochastic relationship of wind power to wind speed and direction are addressed
using Monte Carlo simulation of a VARMA-GARCH model and conditional kernel
density estimation.
Sponsored Session
Chair: Tallys Yunes, Department of Management Science, University of
Miami, Coral Gables, FL, 33124-8237, United States of America,
tallys@miami.edu
1 - Relaxation Based on Multivalued Decision Diagrams
John Hooker, Carnegie Mellon University, Tepper School of Business,
Pittsburgh, PA, United States of America,
john@hooker.tepper.cmu.edu, Sam Hoda, Willem-Jan van Hoeve
4 - Driver Moderator Model - Mining with Domain Knowledge
Ozden Gur Ali, Koc University, Sariyer, Istanbul, Turkey,
oali@ku.edu.tr
We devise an interpretable method that predicts SKU sales as a function of the
pricing, promotion and product availability decisions by the retailers consistently
across similar situations. The method results in interpretable models, leverages
domain knowledge, does concurrent model estimation and feature selection and
relies on data pooling for generalization capability. We evaluate our method with
two multi-store large scale grocery databases from Turkey and the USA.
We solve scheduling problems with a branching method in which a multivalued
decision diagram (MDD) plays the role of both the linear relaxation in mixed
integer programming and the constraint store in constraint programming. We obtain
order-of-magnitude speedups on problems with multiple “among” constraints,
which are used in employee scheduling, assembly line sequencing, etc.
2 - A Logic-Based Benders’ Decomposition Approach for Solving an
Aircraft Maintenance Scheduling Problem
J. Christopher Beck, University of Toronto, 5 King’s College Rd,
Toronto, ON, M5S 3G8, Canada, jcb@mie.utoronto.ca,
Maliheh Aramon Bajestani
We address a flight maintenance problem where the goal is to schedule
maintenance jobs to maximize the expectation that an existing flying program will
have a full complement of aircraft. The schedule must consider the aircraft failure
probabilities and maintenance capacities. We present a logic-based Benders’
decomposition that exhibits multiple orders-of-magnitude improvement over an
existing mixed-integer programming model.
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WA34
3 - Improving the Held and Karp Approach with
Constraint Programming
Willem-Jan van Hoeve, Carnegie Mellon University, 5000 Forbes
Avenue, Pittsburgh, PA, 15213, United States of America,
vanhoeve@andrew.cmu.edu, Michel Rueher, Jean-Charles Régin,
Louis-Martin Rousseau
5 - On the Optimal Control of Large Scale Systems with
Stochastic Interactions
Eugene Perevalov, Lehigh University, Department of Industrial &
Systems Engineerin, Bethlehem, PA, 18017, eup2@lehigh.edu
We study the problem of efficient control of large-scale systems that can be modeled
by a collection of homogeneous elements with stochastic interactions. For the
general case, we formulate the efficient control problem as an inverse inference
problem in Bayesian networks. For the case of systems with a high degree of
uniformity in the element interactions, we propose to use the renormalization
group (RG) approach for the purpose of characterizing the phase structure of the
system and feasibility of efficient control. We give several examples and perform
numerical experiments to check the validity of the proposed approach.
We show that domain filtering algorithms developed for the weighted spanning tree
constraint can be adapted to the Held and Karp procedure to solve the TSP. In
addition, we introduce a special-purpose filtering rule based on the underlying
mechanisms used in Prim’s algorithm. Finally, we explore two different branching
schemes to close the integrality gap.
■ WA34
■ WA35
C - Room 7, Level 3
Joint Session ICS/ Complex/ QSR: Sensing, Prediction
and Prognostics in Complex Systems
Advances in Anomalous Diffusion I
Sponsor: Applied Probability
Sponsored Session
Sponsor: Computing Society/ Complex Systems/ Quality,
Statistics and Reliability
Sponsored Session
Chair: Iddo Eliazar, Professor, Holon Institute of Technology,
P.O. Box 305, Holon, 58102, Israel, eliazar@post.tau.ac.il
1 - Universal Generation of Fractal Statistics
Iddo Eliazar, Professor, Holon Institute of Technology, P.O. Box 305,
Holon, 58102, Israel, eliazar@post.tau.ac.il, Joseph Klafter
Chair: Satish Bukkapatnam, Professor, Oklahoma State University, 318,
Enginnering North, School of Industrial Engineering, Stillwater, OK,
74075, United States of America, satish.t.bukkapatnam@okstate.edu
1 - Willingness-to-Pay Prediction using Empirical Mode Decomposition
and Local Gaussian Process
Satish Bukkapatnam, Professor, Oklahoma State University, 318,
Enginnering North, School of Industrial Engineering, Stillwater, OK,
74075, United States of America, satish.t.bukkapatnam@okstate.edu,
Changqing Cheng, Akkarapol Sa-ngasoongsong
We present a stochastic superposition model which is capable of generating - in a
universal fashion - various “fractal statistics”. The stochastic superposition model is
general and robust, and arises naturally in diverse fields of science and engineering.
Universally-generated “fractal statistics” include: anomalous diffusion - power-law
growth of temporal dispersion; Lévy flights - power-law amplitudinal fluctuations;
1/f noises - power-law temporal correlations.
Prediction of customer preferences over time is important for effective design of a
product portfolio. However, the preferences evolution follows a nonlinear and
nonstationary dynamics. We present two new approaches, based a local gaussian
process (LGP) and empirical mode decomposition (EMD) for accurate prediciton of
customer willingness-to-pay (WTP).
2 - Detecting the Origins of Anomalous Siffusion: P-variation Test and
its Applications
Marcin Magdziarz, Dr, Wroclaw University of Technology,
Wyspianskiego 27, Wroclaw, 50-370, Poland,
marcin.magdziarz@pwr.wroc.pl
2 - Identification of a Mixture of Hidden Markov Models using
Metaheuristic Search
Dragan Djurdjanovic, Assistant Professor, The University of Texas at
Austin, 1 University Station, C2200, ETC 5.122, Austin, TX, 78712,
United States of America, dragand@me.utexas.edu, Michael Cholette
Motivated by growing interest in single molecule spectroscopy, we propose a
method to detect mechanisms leading to subdiffusion. We introduce the so-called pvariation test, which allows distinguishing between two models of subdiffusion on
the basis of one realization of the unknown process. We apply our approach to
experimental data (random motion of an individual molecule inside the E. coli cell).
Mixture of Hidden Markov Models (HMMs) was recently proposed for modeling of
degradation of systems working under variable operating conditions. We present a
method for identification of a mixture of HMMs from a sequence of observations
corresponding to a known sequence of operating conditions. The method utilizes a
metaheuristic search to initialize the Baum-Welch algorithm and maximize the
likelihood of observations.
3 - Aging, Ergodcity Breaking and Universal Fluctuations in Continuous
Time Random Walks
Igor Sokolov, Prof., Humboldt University Berlin, Newtonstr. 15,
Berlin, D-12489, Germany, igor.sokolov@physik.hu-berlin.de
We consider subdiffusive transport within the continuous time random walk
(CTRW) model. The anomalous diffusion under CTRW is a process with nonstationary increments and shows explicit dependence of observables on the time
elapsed from preparing the system in its present state. This corresponds to aging of
the process, leading to death of linear response to an external stimulus and intrinsic
ergodicity breaking. Different manifestations of these properties will be discussed.
3 - Weather Forecasts and Power Grid Operations
Victor Zavala, Argonne National Laboratory, Math and Comp.
Science Div., Bdg 240, 9700 S Cass Ave, Argonne, IL, 60439,
United States of America, vzavala@mcs.anl.gov, Mihai Anitescu,
Emil Constantinescu
We review motivations and challenges arising in the implementation of advanced
numerical weather prediction models in power grid operations. In particular, we
analyze trade-offs between computational bottlenecks, resolution, accuracy, and
economic performance of power systems.
■ WA36
Panel Discussion: Research in Teaching Schools
4 - Binary Code Provenance and Heredity Detection Modeling
and Error Analysis
LiYing Cui, Reserach Assistant, Penn State University, 310 Leonhard
Building, University Park, PA, 16802, United States of America,
luc5@psu.edu, Soundar Kumara
Sponsor: INFORM-ED
Sponsored Session
Moderator: John Kros, Associate Professor of Marketing and Supply
Chain Management, East Carolina University, 3121 Bate Building,
Greenville, NC, 27858, United States of America, krosj@ecu.edu
1 - Panel Discussion: Doing Research at Balanced Model Schools
Panelists:John Kros, Associate Professor of Marketing and Supply
Greenville, NC, 27858, United States of America, krosj@ecu.edu,
Marvin Brown,Assistant Professor of CIS, Grambling University,
403 Main Street, Grambling LA 71245, United States of America,
brownm@gram.edu, Christopher Keller,Assistant Professor of
Marketing and Supply Chain Management, East Carolina University,
3136 Bate Building, School of Business, Greenville NC 27858, United
States of America, kellerc@ecu.edu, Scott Nadler, Assistant Professor,
University of Central Arkansas, COB 312, Conway AR 72035,
United States of America, SNadler@uca.edu
Information in this digital era exists as binary code. Due to the information
explosion in recent years there is a need to detect the lineage among information.
In the cases of malware, it will be necessary identify the variants and to predict the
functionality of future viruses. In this work, we propose a binary code provenance
and heredity detection and prediction method based on CyGene (Gene equivalent
in Cyber engineering) detection. The error analysis of this method is studied
thoroughly based on the ideas of false positives and false negatives.
This is a session set up by the INFORM-ED forum it is a panel on the topic of
“Doing Research at Balanced Model Schools.”
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■ WA37
WA39
2 - Controlling PHEV Recharging Through Effective Electricity
Price Signals
Lizhi Wang, Iowa State University, 3016 Black Engineering, Ames,
IA, 50014, United States of America, lzwang@iastate.edu, Pan Xu
Stochastic Control, Dynamic Games and Their
Applications
We use a bilevel optimization model to design effective electricity price signals to
control PHEV recharging profile. Various studies have shown that uncontrolled
PHEV recharging could have a significant impact on the capacity adequacy, cost
efficiency, and reliability of power systems. Price signals could serve as a demand
management tool to control the recharging activities. Our models will be able to
compare the effectiveness of different price signals.
Sponsored Session
Chair: Hector Jasso-Fuentes, Mathematics Department, CINVESTAV-IPN,
Apartado Postal 14-740, 07000, Mexico DF, Mexico, Mexico,
hjasso@math.cinvestav.mx
1 - Some New Results in Controlled Switching Diffusions
Ari Arapostathis, Professor, University of Texas at Austin,
1 University Station (C0803), Department Electrical and Computer
Eng., Austin, TX, 78712, United States of America,
ari@mail.utexas.edu
3 - A Branch-and-bound Algorithm for the Bilevel Mixed Integer Linear
Programming Problem
Pan Xu, Iowa State University, 3038 Black Engineering, Ames,
United States of America, panxu@iastate.edu, Lizhi Wang, Shan Jin,
Sarah Ryan
We present a new algorithm for the bilevel mixed integer linear programming
problem. This algorithm consists of two levels of branch-and-bound. At the upper
level, we break the non-convex feasibility region into convex pieces. At the lower
level, we solve a linear program with complementarity constraints, which is a
simple case of mathematical program with equilibrium constraints.
We study the stability and ergodic control problems of controlled switching
diffusions, modeled by a coupled system of Ito stochastic differential equations,
under no assumption of irreducibility. Stability is defined as positive recurrence
relative to an open ball in the space of the continuous component. We show among
others that if the model is stable, then the upper envelope of the class of invariant
probability measures is a finite measure, and we study the implications of this
property.
4 - Lateral Transhipment with Customer Switching
Wenjing Shen, Drexel University, 101 N. 33rd Street, Philadelphia,
United States of America, ws84@drexel.edu, Xinxin Hu, Yi Liao
2 - Control of Inventories with Markov Demand
Alain Bensoussan, Research Professor, University of Texas at Dallas,
School of Management, Office 3.211, Dallas, 830688,
United States of America, axb046100@utdallas.edu
We consider a lateral transshipment problem between two retailers where an
uncertain fraction of the unfulfilled demand may switch to another retailer with
inventory. We show that the firm with surplus inventory may not transship all
request inventory and identify conditions when full, partial or no transshipment
takes place. We provide sufficient conditions for a unique Nash equilibrium and
evaluate the impact of customer switching behavior on inventory decisions and
equilibrium profits.
We consider inventory control problems in discrete time. The horizon is infinite, and
we consider discounted payoffs as well non-discounted payoffs (ergodic control). We
may have backlog or not. We may have set up costs or not. We show how the base
stock policy and the s,S policy can be extended.
3 - Overtaking Equilibria for Zero-sum Markov Games
Onesimo Hernandez-Lerma, Prof., CINVESTAV-IPN, Math.
Department, A.Postal 14-740, Mexico D.F. 07000, Mexico,
ohernand@math.cinvestav.mx
■ WA39
We study overtaking (a.k.a. catching-up) optimality for a class of zero-sum Markov
games that includes stochastic differential games, and games with a countable state
space.
Joint Session OPTIM/ ICS:
Sponsor: Optimization/ Computing Society
Sponsored Session
4 - Joint Optimization of Pricing Strategies and Inventory Control with
Continuous Stochastic Demand
Yongqiang Wang, University of Maryland, College Park, 3182 AVW,
College Park, MD, United States of America, yqwang@umd.edu,
Michael Fu, Steven Marcus
Chair: Jeff Linderoth, University of Wisconsin-Madison, 1513 University
Av., Madison, WI, United States of America, linderoth@wisc.edu
1 - Disjunctive Cuts for Convex Mixed Integer Nonlinear
Program (MINLP)
Mustafa Kilinc, Graduate Student, University of Wisconsin-Madison,
3226 Mechanical Engineering Building, 1513 University Avenue,
Madison, WI, 53706, United States of America, kilinc@wisc.edu,
Jeff Linderoth, James Luedtke
We analyze the dynamic pricing problem for inventory systems with price-sensitive
continuous stochastic demands. An analytical solution for a special demand is
provided. For more general demand models, we propose a simulation-based method
for solving the dynamic pricing problem, assuming a finite number of price changes
over the time horizon of interest. In the framework of our simulation-based
algorithm, we can also jointly optimize the price and the initial inventory level.
Stubbs and Mehrotra [1999] generalized the disjunctive cutting plane method of
Balas et al. into a branch-and-cut method for convex MINLPs which generates cuts
by solving a convex projection problem in a higher dimensional space. Thus, it is
computationally expensive to be included in a MINLP solver in practice. Our new
method achieves this by solving a cut generating linear program iteratively.
Computational results shows significant improvements in root node gap closure and
solution times.
■ WA38
Complementarity Problems
2 - New Linear Relaxations for Quadratically Constrained Quadratic
Programming Problems
Mahdi Namazifar, University of Wisconsin-Madison, 1513 University
Ave, Madison, WI, United States of America, namazifar@wisc.edu,
Jeff Linderoth, James Luedtke
Sponsor: Optimization/Linear Programming and Complementarity
(Joint Cluster ICS)
Sponsored Session
Chair: Hande Benson, Associate Professor, Drexel University, Department
of Decision Sciences, LeBow College of Business, Philadelphia, PA, 19104,
United States of America, hvb22@drexel.edu
1 - Single Timescale Regularization Schemes for Monotone
Nash Games
Uday Shanbhag, Asst. Professor, University of Illinois at Urbana
Champaign, Urbana, Il, United States of America,
udaybag@illinois.edu, Aswin Kannan
We study a novel approach to build polyhedral relaxations for nonconvex
quadratically constrained quadratic programming (QCQP) problems. This approach
considers all of the constraints of the problem at once and tries to find tight
relaxations for the problem which are reasonable in size. We present numerical
comparisons in terms of lower bounds and relaxation size.
3 - Inequalities for a Nonseparable Quadratic Set
Hyemin Jeon, University of Wisconsin-Madison, Room 3227,
Mechanical Engineering Bldg., 1513 University Avenue, Madison,
United States of America, jeon5@wisc.edu, Jeff Linderoth
We consider single-timescale schemes for the distributed computation of equilibria
arising from montone Nash games, Specifically, we propose iterative regularization
counterparts of Tikhonov and proximal-point schemes where
regularization/centering parameters are updated after every projection step, rather
than when an approximate solution of the regularized problem is available.
Convergence theory, particularly in limited coordination settings, is presented along
with numerical results.
We consider a nonseparable quadratic set which appears in applications such as
portfolio optimization, and investigate ways to obtain a good approximation of its
convex hull. Our work starts from transforming the set using Cholesky factorization,
and studying its linear outerapproximation to obtain strong valid inequalities. Lifting
plays a vital role in generating these inequalities.
373
WA40
4 - Pooling Problems with Binary Variables
Jeff Linderoth, University of Wisconsin-Madison, 1513 University
Av., Madison, WI, United States of America, linderoth@wisc.edu,
James Luedtke, Claudia D’Ambrosio, Andrea Lodi, Andrew Miller
3 - A Near Optimal Algorithm for Multivehicle Dispatching and Routing
with Time Windows
Ahmed El-Nashar, Doctoral Student, University of Central Florida,
4000 Central Florida Blvd, Orlando, FL, 32816, United States of
America, aelnasha@mail.ucf.edu, Dima Nazzal
The pooling problem is a bilinear program that models linear blending in a network.
Often, pooling problems contain binary variables that model network design issues.
We study how to tighten relaxations of pooling problems with binary variables by
studying the convex hull of simple sets associated with these problems.
We propose a metaheuristic for solving the VRPTW for a depot with limited number
of docks. The metaheuristics clusters customers into groups based on their proximity
to one another. A modified local improvement algorithm is applied to each cluster
to find the best sequence for visiting customers with different dispatching times.
Finally, an assignment problem formulation is used to determine the dispatching
time and the visiting sequence for each vehicle to minimize the total traveled
distance.
■ WA40
Solver APIs II
■ WA42
Cluster: John Forrest-fest | COIN-OR 10th (Joint Cluster Computing)
Invited Session
Computational Optimization and Applications I
Chair: Matthew Saltzman, Clemson University, Department of
Mathematical Sciences, Martin Hall, Box 340975, Clemson, SC, 29631,
United States of America, mjs@clemson.edu
1 - The COIN-OR Open Solver Interface: A Status Report
Matthew Saltzman, Clemson University, Department of
Mathematical Sciences, Martin Hall, Box 340975, Clemson, SC,
29631, United States of America, mjs@clemson.edu
Sponsor: Optimization/Computational Optimization and Software
(Joint Cluster ICS)
Sponsored Session
Chair: Michele Samorani, PhD Candidate, Leeds School of Business,
University of Colorado at Boulder, UCB 419, Boulder, CO, 80309-0419,
United States of America, Michael.Samorani@Colorado.EDU
1 - Solving Hard Combinatorial Optimization Problems as Implicit
Hitting Set Problems
Erick Moreno-Centeno, Assistant Professor, Texas A&M University,
Industrial and Systems Engineering, College Station,
United States of America, e.moreno@tamu.edu, Richard Karp
The Open Solver Interface (OSI) is the oldest multi-solver API in COIN-OR. We
discuss its current status and plans for the future.
2 - A COIN OSI Solver Plugin for Microsoft Solver Foundation
Lou Hafer, Simon Fraser University, Burnaby, BC, V5A 1S6, Canada,
lou@cs.sfu.ca
MsfOsi implements a solver plugin that allows Microsoft Solver Foundation to use
COIN solvers through the OSI API. There are interesting differences in design
philosophy. This talk will examine what it takes to bridge the gap.
The hitting set (HS) problem is: given a set U and a family S of subsets of U, find a
minimum-cardinality set that intersects each set in S. In the implicit HS problem
(IHS), S is given via an oracle which verifies that a given set is a HS or returns a
not-intersected set from S. Many NP-hard problems can be solved as IHS. We solve
IHS by combining efficient heuristics and exact methods. We present computational
results for the minimum-feedback-vertex-set and the maximum-weight-trace
problems.
3 - The Optimization Services Solver Interface
Kipp Martin, University of Chicago, 5807 South Woodlawn, Chicago,
IL, 60637, United States of America, kmartin@chicagobooth.edu
In this talk we describe how to use the Optimization Services (OS) project to
interface with COIN-OR solvers. The OS interface is quite flexible and allows the
user to generate linear and nonlinear instances for solvers. In addition, there is an
interface for solver options and solver results.
2 - Envy Quotes and the Iterated Core-Selecting Combinatorial Auction
Abraham Othman, Graduate Student, Computer Science
Department, Carnegie Mellon University, 5000 Forbes Ave,
Pittsburgh, PA, 15213, United States of America,
aothman@cs.cmu.edu, Tuomas Sandholm
We describe an iterated combinatorial auction in which the allocation and prices
converge to a solution in the core of the agents’ true valuations. In each round of
the iterative mechanism, agents act on hints that suggest the prices of the bundles
they are interested in. Prior work has required agents to have perfect information
about every agent’s valuations to achieve a solution in the core. Here a core solution
is reached even in the private value setting.
■ WA41
Vehicle Routing I
Contributed Session
3 - Data Mining Driven Neighborhood Search
Michele Samorani, PhD Candidate, Leeds School of Business,
University of Colorado at Boulder, UCB 419, Boulder, CO, 803090419, United States of America, Michael.Samorani@Colorado.edu,
Manuel Laguna
Chair: Ahmed El-Nashar, Doctoral Student, University of Central Florida,
4000 Central Florida Blvd, Orlando, FL, 32816, United States of America,
aelnasha@mail.ucf.edu
1 - Efficient School Bus Routing for Special Needs Students
Behrooz Kamali, University of Arkansas, 4207 Bell Engineering
Center, Fayetteville, AR, 72701, United States of America,
bkamali@uark.edu, Ed Pohl, Scott J. Mason
Metaheuristic approaches based on neighborhood search escape local optimality by
applying predefined rules and constraints. Our general approach learns (offline) the
guiding constraints that, when applied online, will result in effective escape
directions from local optima. The user must define the neighborhood and provide
an attribute representation of a solution and of a pair of solutions. We show our
results on a set of task allocation and matrix bandwidth minimization problems.
Special needs and medically fragile students ride specialized buses to and from
school daily. Unfortunately, special needs service-to-school assignments are often
made without any consideration of a student’s geographical location. We present
optimization models that seek to improve administration-based performance metrics
via smarter network assignments and effective bus routing decisions.
2 - A New Capacitated Path Covering Problem
Macarena Donoso, PhD Student, Diego Portales University, Ejercito
441, Santiago, Chile, macarena.donosop@gmail.com, Ignacio Basulto
We formulated and solve a particular capacitated vehicle routing problem. A path is
built between two points of the network, for every vehicle of the fleet. Every route
exceeds neither the vehicle capacity nor the maximum time of the trip. The
objective is minimize the travelling cost. The nodes that to be not covered, must be
inside a distance coverage to the the network. We propose an integer programming
formulation and, an heuristic algorithm of resolution based on ants colonies was
developed.
374
■ WA44
WA47
2 - A Bilevel Model for Designing Preventive Healthcare
Facility Networks
Yue Zhang, Assistant Professor, The University of Toledo, 2801 West
Bancroft Street, Toledo, OH, 43606, United States of America,
Yue.Zhang@sauder.ubc.ca, Oded Berman, Vedat Verter,
Patrice Marcotte
C - Room 2, Level 2- Mezzanine
Resource Allocation in Healthcare
Sponsor: Health Applications
Sponsored Session
This paper presents a methodology for designing a network of preventive healthcare
facilities to improve its accessibility to potential clients, so as to maximize
participation to preventive healthcare programs. We formulate the problem as a
mathematical program with equilibrium constraints. We use the model to analyze
an illustrative case, the network of mammography centers in Montreal. A number
of interesting results and managerial insights are discussed.
Chair: David Hutton, Stanford University, Palo Alto, CA,
United States of America, billdave@stanford.edu
1 - Cost-Effectiveness of Screening and Treating Acute HIV Infection in
Men Who Have Sex with Men
Jessie Juusola, PhD Candidate, Stanford University, Dept of
Management Science & Engineering, 499 Terman Engineering
Center, Stanford, CA, 94305, United States of America,
jjuusola@stanford.edu, Eran Bendavid, Doug Owens, Margaret
Brandeau, Elisa Long
3 - Inferring Model Parameters in Network-based Disease Simulation
Eva Enns, Stanford University, 117 Encina Commons, Stanford, CA,
94035, United States of America, evaenns@stanford.edu,
Margaret Brandeau
Given the highly infectious nature of acute HIV infection, identifying and treating
acutely infected individuals could play a significant role in reducing HIV
transmission. We develop a dynamic compartmental model of the HIV epidemic in
the US to estimate the costs and health benefits of screening for acute infection and
treating acutely infected men who have sex with men. We find such programs likely
to be a cost-effectiveness method of reducing the burden of HIV in this high-risk
group.
Many models of infectious disease ignore the underlying contact structure through
which the disease spreads. However, in order to evaluate the efficacy of certain
disease control interventions, it may be important to include this network structure.
We present a network modeling framework of the spread of disease and a
methodology for inferring important model parameters, such as those governing
network structure and network dynamics, from readily available data sources.
4 - The Mayo Clinic Optimizes Patient Transport Staffing
Dustin Kuchera, MS, Business Analyst, Mayo Clinic, 626 8th St SW,
Rochester, MN, 55902, United States of America,
kuchera.dustin@mayo.edu, Thomas R. Rohleder, PhD
2 - Initiatives Management in Public Healthcare Administration
Zehra Bilginturk Yalcin, University of Texas, Austin, Operations
Research and Industrial Eng, Graduate Program, Austin, TX, 78712,
United States of America, zehra.yalcin@gravitant.com, Ilyas M. Iyoob
In this paper, we report on the implementation of simple integrated queuing and
mathematical programming methods to optimize staffing for patient transport at the
Mayo Clinic. A tool was developed and implemented in Microsoft Excel and Visual
Basic for Applications and includes an easy-to-use interface. Results of the
implementation include significant staff savings via more efficient scheduling.
A Public Healthcare Administration agency in a large state in the US is constantly
running multiple initiatives within the organization. The agency faces the issue of
selecting, prioritizing and scheduling initiatives based on the objectives of interest at
the time, while maintaining dependencies between initiatives as well as limited
resources and Federal budget constraints. The problem is modeled as an MIP and
serves as a useful decision support tool in Public Healthcare Administration.
5 - Prioritization of Medical Equipment for Maintenance Decisions
Sharareh Taghipour, PhD Candidate, University of Toronto,
5 King’s College Road, Toronto, ON, M5S 3G8, Canada,
sharareh@mie.utoronto.ca, Dragan Banjevic, Andrew K.S. Jardine
3 - Modeling Cost-Effectiveness Data for Medical Decision Making:
A Statistical Framework
Megan DeFauw, University of Michigan, mcdefauw@umich.edu,
Vijayan Nair, Joseph Norman, Allison Rosen
Clinical engineering departments in hospitals are responsible for establishing and
regulating a Medical Equipment Management Program to ensure that medical
devices are safe and reliable. To mitigate functional failures, significant and critical
devices should be identified and prioritized. We present a multi-criteria decisionmaking model to prioritize medical devices according to their criticality.
The effect of treatment on cost and QALYs in CEA is determined through simulation
or a clinical study. In either case, the mean cost-effectiveness ratio is a poor
characterization of treatment effect. We develop a statistical framework exploiting
the stochastic evolution of disease processes over time to characterize the effect of
treatment and also exploit the concept of stochastic dominance to aid in decisionmaking when the utility function is unknown. Finally, we illustrate with an
example.
■ WA47
New Directions in Project Management
■ WA45
Cluster: Topics in Project Management
Invited Session
Pierskalla Finalists V
Chair: Willy Herroelen, Emeritus Professor, K.U.Leuven, Research Center
for Operations Management, Department of Decision Sciences &
Information Management, Naamsestraat 69, Leuven, B-3000, Belgium,
willy.herroelen@econ.kuleuven.be
1 - A New Approach for Project Risk Analysis
Stefan Creemers, K.U.Leuven, Research Center for Operations
Management, Department of Decision Sciences & Information
Management, Naamsestraat 69, Leuven, B-3000, Belgium,
stefan.creemers@econ.kuleuven.be, Erik Demeulemeester,
Stijn Van de Vonder
Sponsored Session
Chair: Mariel Lavieri, Assistant Professor, University of Michigan, 1205
Beal Avenue, Ann Arbor, MI, 48109-2117, United States of America,
lavieri@umich.edu
1 - Real-time Differentiation of Nonconvulsive Status Epilepticus From
Other Encephalopathies using Quantitative EEG Analysis:
A Pilot Study
Jicong Zhang, PhD Candidate, University of Florida, 303 Weil Hall,
ISE Department, Gainesville, FL, 32611, United States of America,
jicong@ufl.edu, Panos Pardalos, Chang-Chia Liu, Petros
Xanthopoulos, Scott Bearden, Basim M. Uthman
Most quantitative project risk analysis techniques provide insight in the risk profile
of the project and in the feasibility of certain project completion dates. Far fewer
efforts exist that aim at identifying the underlying risk factors that cause the project
schedule to slip. We introduce an approach to calculate the impact that each risk
has on the project completion date. Such an approach allows to focus mitigation
efforts on those risks whose mitigation would be most effective.
Generalized NonConvulsive Status Epilepticus (NCSE) and some non-epileptic
encephalopathies have similar clinical symptoms and exhibit similar EEG
waveforms. To distinguish NCSE from some non-epileptic encephalopathies is
difficult and significant clinically. Nonlinear dynamics are extracted from EEG and
classifiers are designed to differentiate NCSE and toxic/metabolic encephalopathy.
The results showed strong evidence that nonlinear dynamic measures can be useful
in clinical diagnosis of NCSE.
2 - On the Interaction Between Railway Scheduling and Resource
Flow Networks
Erik Demeulemeester, Professor, KU Leuven, Naamsestraat 69,
Leuven, B-3000, Belgium, erik.demeulemeester@econ.kuleuven.be,
Wendi Tian
In previous research, we have shown that in realistic situations railway scheduling
improves both the stability and the expected project length over roadrunner
scheduling. In this research, we introduce the concept of resource flow networks
and analyze what the impact is of the resulting combinations on average project
length, its standard deviation, the timely project completion probability and the
stability cost. Extensive computational results will be presented on small and larger
projects.
375
WA48
3 - Proactive Execution Policies for the Stochastic RCPSP
Filip Deblaere, KU Leuven, Naamsestraat 69, Leuven, B-3000,
Belgium, filip.deblaere@econ.kuleuven.be, Erik Demeulemeester,
Willy Herroelen
3 - Collaborative Information Acquisition (Talk)
Danxia Kong, The University of Texas at Austin,
1 University Station, Austin, TX, 78712, United States of America,
Danxia.Kong@PhD.mccombs.utexas.edu, Maytal Saar-Tsechansky
We propose a methodology for the determination of a project execution policy for
the stochastic RCPSP that attempts to minimize the project execution costs, defined
as the sum of the expected costs due to activity starting time deviations and the
expected penalties or bonuses associated with late or early project completion. We
show that our approach significantly outperforms existing proactive scheduling
procedures for resource-constrained projects with uncertain activity durations.
Most information acquisition policies aim to improve the predictive accuracy of a
model. However, in practice, a predictive model is used with other models to inform
arbitrarily complex decisions. This paper discusses a new kind of collaborative
information acquisition (CIA) policies, where multiple predictive models
collaboratively prioritize information acquisitions to promote the decisions they
inform. We present a framework and a specific CIA policy that yields superior
decision performance.
■ WA48
■ WA50
C -Room 11, Level 2- Mezzanine
Software Demonstrations
Managing Workload Dependencies in the Cloud
Cluster: Software Demonstrations
Invited Session
Cluster: Cloud Computing
Invited Session
1 - FICO - Building Optimization Applications in Xpress
Oliver Bastert, Product Management, FICO, 901 Marquette Avenue,
Suite 3200, Minneapolis, MN, 55402, United States of America
Chair: Hani Jamjoom, IBM Research, 19 Skyline Dr., Hawthorne,
United States of America, jamjoom@us.ibm.com
1 - Uncovering Causal Factors in HPC Workloads
Anshul Sheopuri, Research Staff Member, IBM TJ Watson Research
Center, 19 Skyline Drive, Hawthorne, United States of America,
sheopuri@us.ibm.com, Zon-yin Shae, Eric Shiu, Hani Jamjoom
This tutorial will focus on developing and deploying complete optimization
applications using FICO’s array of mathematical modeling and optimization tools.
These tools can be used for modeling, solving, analyzing and visualizing
optimization problems, and integrating them seamlessly in business applications.
During this tutorial, Bastert will explain how Xpress-Mosel, Xpress-IVE and XpressApplication Developer can decrease development time for new optimization
applications and enable you and your customers to make smarter decisions. The
proven technologies offered by FICO can be used in range of applications such as
supply chain management, transportation, finance, energy, manufacturing, retail,
insurance and manufacturing industries, to name a few.
Scheduling and Pricing engines are critical components of a High Performance
Computing (HPC) system. To deploy these engines in a HPC system, it is important
to understand the causal factors of demand fluctuations - number of users, time of
day, time of month, etc. The objective of our work is to bring scheduling and pricing
models in HPC to market by validating or invalidating the assumptions used for
developing these models by uncovering the causal factors of demand fluctuations.
2 - Palisade Corporation - DecisionTools Suite Software Introduction
Thompson Terry, Senior Risk Analyst, Trainer, Consultant, Palisade
Corporation, 798 Cascadilla Street, Ithaca, NY, 14850, United States
of America, tterry@palisade.com
2 - Using Application Dependencies for Workload Migration Decisions
in Cloud Datacenter Environments
Petros Zerfos, Research Staff Member, IBM T.J. Watson Research
Center, 19 Skyline Drive, Hawthorne, NY, 10532, United States of
America, pzerfos@us.ibm.com, Hani Jamjoom, Yew Huey Liu,
Kang-Won Lee, Vivek Shrivastava
Palisade’s DecisionTools Suite includes 7 software packages that can be used by a
wide variety of departments and individuals within any organization to better assess
risk and make well-informed decisions. This comprehensive example demonstrates
how all the components of the Suite can be used together to assess the likelihood of
success of a new product launch, determine critical variables to limit risk exposure,
optimize the inclusion of the new product into existing manufacturing facilities, and
plan for the expansion of both production and distribution networks.
Virtual machine (VM) migration can optimize the use of physical servers in cloud
datacenters. Enterprise applications consist of multiple interdependent VMs. Current
research optimizes for intra-server constraints (e.g., CPU); it ignores inter-server
dependencies (e.g., network communication). Our work formulates the VM
migration problem to also account for inter-VM dependencies, and proposes an
online approximation. Using workloads from a datacenter, we explore the efficacy
of our solution.
■ WA49
3 - Overdriver: Enabling High Data Center Utilization Through
Aggressive Memory Oversubscription
Dan Williams, Cornell University, 4104 Upson Hall, Ithaca, NY,
14853, United States of America, djwill@cs.cornell.edu,
Hani Jamjoom, Yew Huey Liu, Hakim Weatherspoon
Machine Learning and Business Intelligence
Sponsor: Information Systems
Sponsored Session
With the intense competition between cloud providers, resource oversubscription is
essential for achieving higher utilization and profits from the underlying
infrastructure. Resource oversubscription, however, comes at a price: it increases the
likelihood of overload due to insufficient physical resources. We present Overdriver,
a system that aggressively oversubscribes memory and immediately reacts to
mitigate the effects of all types of overload, including transient overload.
Chair: Maytal Saar-Tsechansky, Assistant Professor, University of Texas at
Austin, 1 University Station, Austin, 78712, United States of America
1 - Active Inference and Active Learning for Data Streams
Foster Provost, Professor, New York University, 44 West 4th Street
#8-86, New York, NY, 10012, United States of America,
fprovost@stern.nyu.edu, Josh Attenberg
We consider applications where predictive models are applied to a stream of
instances that can repeat, such as web pages for ad impressions, and where there is
a budget for applying human resources to acquire ground truth labels for carefully
chosen instances—both for learning and for direct inference (in lieu of using the
predictive model). We introduce strategies for allocating human resources, which
consider: p(x), which may be highly skewed; error cost; and the value for (active)
learning.
2 - Bias in Cross Validation
Claudia Perlich, Chief Scientist, Media 6 Degrees, 16 Oakrdige Rd,
Mt Kisco, United States of America, claudia@media6degrees.com,
Grzegorz Swirszcz
Evaluation of model performance has a long tradition in statistics and machine
learning. Non-parametric estimations of model performance include bootstrapping,
jackknife, random sub-sampling and cross-validation. We show that cross-validation
to data with low signal can lead to `holdout’ predictions with perfectly opposite
ranking. While such a `model’ would raise suspicion, great harm can be done if it is
integrated in an automated process that includes stacking or ensemble selection
methods.
376
■ WA51
WA53
allows the very fast solution of problems in which up to 50000 scenarios are used to
characterize uncertainty. Applications to defense and homeland security problems
will be discussed.
Optimal Routing Through Military Networks
2 - Army Research Office Program - Decision and Neural Sciences
Janet Spoonamore, Army Research Office, P.O. Box 1221,
Research Triangle Park, NC, 27709, United States of America,
janet.spoonamore@us.army.mil
Sponsor: Military Applications
Sponsored Session
Chair: Chris Odom, ENS, US Navy, Colorado School of Mines,
Engineering Hall 816 15th Street, Golden, CO, 80401, United States of
America, codom@mines.edu
1 - Routing and Scheduling Supply Ships for the Combat
Logistics Force
Gerald Brown, Operations Research Department, Naval Postgraduate
School, Monterey, CA, 93943, United States of America,
ggbrown@nps.navy.mil, Matthew Carlyle, Patrick Burson, Jeff Kline,
Anton Rowe
The Decision and Neuro Sciences program addresses development of new advanced
modeling, simulation, optimization and other analysis methodologies to support
command-level decision-making at the operational level. The program includes two
thrusts - one addressing advanced numerical methods - especially addressing
stochastic behaviors and second addressing modeling of cognitive and neural
phenomenology of decision making.
3 - Tactical Behavior Composition
Evan Clark, Intelligent Automation, Inc., 15400 Calhoun Drive,
Suite 400, Rockville, MD, 20855, United States of America,
eclark@i-a-i.com, Jeffrey Smith
We synchronously route a fleet of supply ships between ports and combatant
customer ships throughout an area of operations, or worldwide. Key concerns
include keeping combatant inventories above required operational safety stock
levels, minimizing port visit and other supply ship costs, sourcing costs, and the cost
of fuel consumed. We show how the system works and what we have learned in
practice along with our Military Sealift Command sponsor.
Behavior composition for computer generated forces is a technique that facilitates
the creation and validation of agent behavior. It refers to the practice of creating
reusable primitives that can be combined to construct new complex agent
behaviors. Research in behavior composition has often focused on the use of
procedural primitives. This paper discusses a framework for commander agent
behavior composition that includes not only procedural primitives, but also those
representing tactical concepts such as spatial relationships, subordinate coordination,
terrain analysis, firepower and mobility. These primitives give the domain expert the
ability to influence the manner in which tactical decisions are made. These
primitives are elements of a tactics description language called Tesla Using the Tesla
language, a tactical behavior expert composes tactic templates which can later be
used by commander agents in course of action development and to solve tactical
problems.
2 - Interdicting Networks to Competitively Minimize Evasion with
Synergy Between Applied Resources
Brian Lunday, Assistant Professor, Department of Mathematical
Sciences, U.S. Military Academy, Department of Math. Sci.
(Building 601), United States Military Academy, West Point, NY,
10996, United States of America, lunday@vt.edu, Hanif Sherali
We examine the problem of minimizing the maximum probability of evasion by an
entity traversing a network from a given source-and-terminus, incorporating novel
forms of superadditive synergy between resources applied to arcs in the network.
We propose an alternative model for sequential overt and covert deployment of
subsets of interdiction resources, and conduct comparative analyses between models
for purely overt (with or without synergy) and composite overt-covert strategies.
4 - Resource-constrained Project Scheduling Under Uncertainty:
Models, Algorithms and Applications
Haitao Li, University of Missouri - St. Louis, 229 CCB, One
University Blvd, St. Louis, MO, 63121, United States of America,
lihait@umsl.edu
3 - New Results on the Network Diversion Problem
Christopher Cullenbine, PhD Candidate, Colorado School of Mines,
1500 Illinois Street, Golden, CO, 80401, United States of America,
ccullenb@mines.edu, Kevin Wood, Alexandra Newman
This research studies the stochastic resource-constrained project scheduling problem
(SRCPSP), which has a wide range of applications in machine scheduling, supply
chain design, project portfolio optimization and personnel/manpower optimization.
The SRCPSP is modeled as a Markov decision process (MDP) to cope with both
structural and non-structural randomness. Techniques from optimization, artificial
intelligence, simulation and statistics are built into an approximate dynamic
programming (ADP) framework to tackle the “curses of dimensionality”.
Preliminary computational results on the deterministic RCPSP are promising.
The network-diversion problem seeks a minimum-weight, minimal s-t cut in a
graph that contains a pre-specified edge. The problem arises in intelligencegathering and war-fighting scenarios. We use Lagrangian relaxation with a stronger
integer linear-programming formulation to modify edge weights for near-minimumweight cut enumeration. We also describe new NP-completeness results,
polynomially solvable special cases, and provide computational results that show
improvements over the original.
■ WA53
4 - Routing Military Vehicles in a Threat Environment Accounting for
Arc-Dependent Risk Costs
Chris Odom, ENS, US Navy, Colorado School of Mines, Engineering
Hall 816 15th Street, Golden, CO, 80401, United States of America,
codom@mines.edu, Alexandra Newman, Kevin Wood
Marketing
Contributed Session
Chair: Nancy Ryan, Associate Professor of Marketing, St. Edward’s
University, 3001 South Congress Avenue, Austin, TX, 78701,
United States of America, nancym@stedwards.edu
1 - Differences Between Imagers and Verbalizers in Users’
Preference-making
Sangwon Lee, The Pennsylvania State University, 343 Leonhard
Building, University Park, PA, 16802, United States of America,
sangwon.advance@gmail.com, Richard Koubek
A directed graph with nodes representing waypoints and sets of arcs denoting paths
for vehicle transit models the area of operations. We develop an integer program
and modify an enumeration algorithm to determine a path that maximizes the
probability of mission success subject to flow balance and side constraints. We
account for arc-dependent risk costs for the case in which a threat contributes risk
to two or more arcs, and we provide preliminary numerical results.
■ WA52
Understanding target users is a crucial issue in establishing design and marketing
strategies for computer-based applications. To contribute to the comprehension of
target users, this study examines the effects of cognitive style (imagers vs.
verbalizers) on user preference based on usability and aesthetics through an
experiment using four simulated systems with different levels of usability and
aesthetics.
Decision Support for Military Operations
Cluster: Homeland Security and Defense
Invited Session
2 - The Market Entry Decision Based on Time-series Country Efficiency
Gary Chao, Kutztown University, P.O. Box 730, Kutztown, PA,
19530, United States of America, chao@kutztown.edu, Maxwell Hsu
Chair: Janet Spoonamore, Army Research Office, P.O. Box 1221,
Research Triangle Park, NC, 27709, United States of America,
janet.spoonamore@us.army.mil
1 - Solution Method for Large Scale Chance-constrained Problems Application Potential to Defense and Homeland Security Problems
Miguel Lejeune, George Washington University, 2201 G Street, NW
Funger 415, Washington, DC, 20052, United States of America,
mlejeune@gwu.edu
Companies may examine country ranking reports before they expand business
operations abroad. Most reports focus on some socio-economic variables and
compute the country ranking results using a weighted averaging method. This
research picks up an attractive foreign market by taking advantage of the data
envelopment window analysis (DEWA) in finding a relatively more efficient
marketplace to invest. We apply to evaluate the efficiency of 22 countries based on
the globalEDGE data from 2002 to 2008.
We introduce a new method for the solution of chance-constrained problems. It is
based on the extraction of patterns which define sufficient/minimal conditions for
the chance constraint to hold and allows the exact reformulation of the stochastic
problem as a linear problem. The method is computationally very efficient and
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WA54
3 - Let Me Stack Them Up: An Analysis of Internet Marketing
Service Contract
Ryan Choi, PhD Student, University of California, Irvine, 6454
Adobe Circle, Irvine, CA, United States of America, jihungc@uci.edu
5 - Inter-institutional Relationships and Emergency Management
Fred Phillips, Professor, Alliant International University, and General
Informatics LLC, 10622 Sunset Ridge Drive, San Diego, CA, 92131,
United States of America, fp@generalinformatics.com
We examine two service contracts which Amazon.com offers to its competing
sellers; i.e., Selling on Amazon (SOA) and Fulfillment by Amazon (FBA). We
analyze how Amazon is incentivized to offer one or both of these contracts.
Compared to pure competition, either contract is more likely offered when
consumers’ valuation gap gets small. Assuming that this valuation gap disappears
once a contract is signed up, Amazon’s contracting decision varies depending on
which seller has a cost advantage.
Public disasters from the Exxon Valdez spill to the US mortgage meltdown involve
many agencies. In improved networks of institutions, the fox will not guard the
henhouse, accountability is enhanced rather than clouded, and remediation is
quick, with blame assigned later. This paper advocates a new field of HighPerformance Inter-Organizational Interaction (HPII). It maps dimensions of HPII
against an extended Multiple Perspectives schema. Recent disasters and research
directions are discussed.
4 - Attracting Customers with Attractive Signage and Architecture
Nancy Ryan, Associate Professor of Marketing, St. Edward’s
United States of America, nancym@stedwards.edu, Helene Caudill
■ WA55
Retail establishments should not overlook the importance of signage and
architecture. We conducted a laboratory study using over 125 students who
reviewed the exterior signs and architecture of five different restaurants. Results
reveal how important these two features are in terms of customers’ intentions to eat
there.
New Product Innovation Strategy
Sponsor: Technology Management/New Product Development
Sponsored Session
Chair: Sreekumar Bhaskaran, Assistant Professor,
Southern Methodist University, 6212 Bishop Blvd, Dallas, TX, 75205,
United States of America, sbhaskar@mail.cox.smu.edu
1 - Managing Delegated Search Over Design Spaces
Sanjiv Erat, University of California San Diego, San Diego, CA,
United States of America, serat@ucsd.edu, Vish Krishnan
■ WA54
Technology Assessment and Forecasting II
Organizations increasingly seek solutions to open-ended design problems by
employing an approach where the search over a solution space is delegated to
outside agents. We study this new class of problems, and through an analytical
model, we examine the relationship between problem specification, award
structure, and breadth of solution space searched by outside agents towards
characterizing how a firm should effectively manage such open-ended design
contests.
Sponsored Session
Chair: Fred Phillips, Professor, Alliant International University, Avenue of
Nations, San Diego, CA, 92131, United States of America,
fphillips@alliant.edu
1 - How do Small Biotechnology Firms Innovate? The Cases
From Taiwan
Yu-Shan Su, Associate Professor, National Taiwan Normal University,
162, HePing East Road, Section 1, Taipei, 106, Taiwan - ROC,
bellesu222@yahoo.com.tw
2 - Drivers of Value and Growth: An Examination of Innovation in the
Solar Energy Supply Chain
Jane Davies, University of Cambridge, Judge Business School,
Trumpington Street, Cambridge, CB2 1AG, United Kingdom,
j.davies@jbs.cam.ac.uk, David Kirkwood
How do small firms innovate? How do a small firm’s internal capabilities and
external alliances contribute to its innovativeness? The main purpose of this study is
to adopt theoretical angle of open innovation to discuss small biotechnology firms in
Taiwan. This study offers an integrated perspective of open innovation in the
literature.
The introduction of government incentives has seen a plethora of firms enter the
solar sector. These include both start-ups and firms diversifying from other
industries. Along with incumbents, these firms face the dual pressures of reducing
production costs while increasing the technology efficiency of solar power. We
combine secondary data and case study analysis of 70 solar firms to show that
process and technological innovation have differential effects on revenue growth
and market value.
2 - Forecasting Timely Revolutions in Organizational Performance
Charles Weber, Associate Professor, Portland State University, P.O.
Box 751, Engineering and Technology Management, Portland, OR,
97207, United States of America, charles.weber@etm.pdx.edu,
Nitin Mayande
3 - Design and Introduction of Conspicuous Durable Products
Vishal Agrawal, Georgia Institute of Technology, 800 W Peachtree St
NW, Atlanta, GA, United States of America,
Vishal.Agrawal@mgt.gatech.edu, Stylianos Kavadias, Beril Toktay
It has been shown that subsystem-level learning activities and firm-exogenous
learning activities can induce delayed, timely revolutions in organizational
performance. This paper develops a method for forecasting revolutions in
organizational performance in an open innovation system. Firm-internal and firmexternal factors are taken into consideration.
We study the implications of exclusivity-seeking consumer behavior on the design
and introduction decisions for a durable product, namely the durability and pricing
choices of the firm. We draw upon the traditional market models of vertically
differentiated durable products to incorporate exclusivity-seeking behavior, and
show that firms should instead consider designing products that undergo slow value
erosion in conjunction with a high-price, low-volume product introduction strategy.
3 - Forecasting the Development of Clean Coal and Natural
Gas Technologies
Christopher Ordowich, SRI International, 1100 Wilson Blvd,
Arlington, VA, United States of America,
christopher.ordowich@sri.com, John Chase
4 - Product Introduction Timing for Start-ups
Sinan Erzurumlu, Assistant Professor, Babson College, Tomasso 123,
Babson Park, MA, 02457, United States of America,
serzurumlu@babson.edu, Sreekumar Bhaskaran, Karthik
Ramachandran
This study estimates the costs and efficiencies of several types of coal and natural gas
power plants with and without carbon capture technologies through 2050.
Improvements in plant efficiency and reductions in capital and O&M costs are
modeled using technology learning curves established by a detailed analysis of
historic performance data. Combined with demand and input cost forecasts, the
learning curves were used to project the cost and adoption of each plant type over
time.
We study how a start-up organization should structure its development process.
While cash constraints pressure the firm to launch a product as soon as possible (to
avoid or delay bankruptcy), it could affect the future products. We develop optimal
policies for the start-up firm to determine whether and when to launch an existing
product under technological uncertainty about future development of products.
4 - Exploring the Societal Dimensions of IT: A Look at the Future of
Sustainable IT Services
Robert Harmon, Professor of Marketing & Technology Management,
Portland State University, P.O. Box 751, Portland, OR, 97207,
United States of America, harmonr@pdx.edu, Haluk Demirkan
Green IT, the first wave of sustainable IT, developed strategies for reducing energy
costs and carbon footprints, primarily in data centers. Green IT has been productoriented and internally focused within the IT function. The second wave of
sustainable IT will be service-oriented and focused beyond the IT function to serve
the organization’s business ecosystem and society at large. This work explores the
key dimensions driving the development and applications of sustainable IT services.
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■ WA56
WA58
3 - Optimal Portfolio Strategy with Liquidity Capacity
Wei Chen, Analytical Solutions Manager, SAS Institute Inc., SAS
Campus Dr., Cary, NC, 27513, United States of America,
Wei.Chen@sas.com
C - Room 1, Level 1
Simulation Optimization and Global Optimization of
Expensive Functions
Liquidity is essential for banks to maintain long-term viability. An optimal portfolio
strategy should not only manage the cash flow gaps but also provide adequate low
cost contingent funding sources in distressed events. This paper proposes a model of
finding minimal cost portfolio with a chance constrained level of positive excess
cash flow and self-sustaining liquidity capacity. The model results in a tractable
linear programming problem using the scenario based approach.
Sponsor: Simulation Society
Sponsored Session
Chair: Peter Frazier, Assistant Professor, Cornell University, 232 Rhodes
Hall, Ithaca, NY, 14853, United States of America, pf98@cornell.edu
1 - Simulation-Optimization Methods for Resource Allocation to
Achieve Equity
Muer Yang, University of Cincinnati, Dept of QAOM, College of
Business, Cincinnati, OH, 45221, United States of America,
yangmr@mail.uc.edu, Theodore Allen, Michael Fry, David Kelton
■ WA58
C - Room 3, Level 1
Finance-Risk Management
This paper uses simulation-optimization models to allocate limited resources under
uncertainty to achieve equity. By equity, we mean that all jobs, customers, etc.
should have approximately equivalent performance measures (e.g., time in queue).
We can provide probabilistic guarantees of global optimality for these allocations.
We present one possible application of this work in allocating voting machines to
precincts for local and national elections.
Contributed Session
Chair: D.J. Alexander-Houle, Adjunct; Program Manager, University of
Phoenix, HP, 14207 Torrey Vista Dr, Houston, TX, 77014, United States of
America, dahoule@sbcglobal.net
1 - A Coherent Valuation Approach for Valuing Risky Projects
S. Reza Seyedshohadaie, Texas A&M University, 3131 TAMU,
College Station, United States of America, sreza@tamu.edu,
Sergiy Butenko, Ivan Damnjanovic
2 - Global Optimization with Reponse Surfaces for Expensive
Simulation Models
Christine Shoemaker, Professor, Cornell University, 210 Hollister
Hall, Cornell University, Ithaca, NY, 14853, United States of America,
cas12@cornell.edu
We present a coherent valuation approch for valuing risky projects in partially
complete markets. The model is based on the exposure to risk and the trade-off
between risk and reward. We demonstrate the application of the model on a largscale engineering project.
We will describe an effective algorithm for global optimization of simulation models
that are computationally expensive and apply it to several problems, including an
environmental simulation model involving systems of nonlinear partial differential
equations. We will demonstrate applications of up to 30 decision variables.
2 - Estimation Error Reduction in Portfolio Optimization with
Conditional Value-at-Risk
Gah-Yi Vahn, PhD Student, UC Berkeley, 4141 Etcheverry Hall,
Mail Code 1777, Berkeley, CA, 94704, United States of America,
gyvahn@berkeley.edu, Andrew Lim
3 - Noise-Tolerant Bayesian Bisection
Peter Frazier, Assistant Professor, Cornell University, 232 Rhodes
Hall, Ithaca, NY, 14853, United States of America, pf98@cornell.edu,
German Gutierrez, Shane Henderson
We introduce a novel method of obtaining robust solutions to data-driven portfolio
optimization with Conditional Value-at-Risk (Expected Shortfall). This method can
be interpreted as penalizing model uncertainty in the optimization problem. We
present some analysis of the method and empirical results that show the superior
performance of this method when the underlying log-return data is both wellbehaved (multivariate Gaussian) and heavy-tailed (multivariate t).
We consider the stochastic optimization problem where we observe noisy
derivatives of the objective function. These derivatives observations are expensive to
obtain, and so our goal is to optimize the function as accurately as possible with a
bounded number of observations. We derive the optimal sequential sampling policy
using dynamic programming for a simplified version of this problem, and then
discuss the use of this policy in the original problem.
3 - Dynamic Models for Consumer Default Risk
Jonathan Crook, Professor, University of Edinburgh, Credit Research
Centre, Business School, 50 George Square, Edinburgh, EH10 4SW,
United Kingdom, j.crook@ed.ac.uk, Tony Bellotti
■ WA57
C - Room 2, Level 1
This talk explains the use of survival analysis for the prediction of default for
consumer loans. The talk will explain how macroeconomic variables can be
incorporated into the model and show results from the parameterisation of such a
model and the predictive performance of it using a data set relating to credit cards.
The model is used to stress test the portfolio of loans using Monte Carlo simulation
to estimate the Value at Risk and Expected Shortfall of the portfolio.
Recent Advances in Portfolio Optimization
Sponsor: Financial Services Section
Sponsored Session
Chair: Chaithanya Bandi, Massachusetts Institute of Technology, 77 Mass
Ave, Cambridge, MA, 02139, United States of America, cbandi@mit.edu
1 - Fairness in Multi-account Optimization with Transaction Costs
Dan Iancu, Stanford University, Stanford GSB, Stanford, CA, United
States of America, Iancu_dan@gsb.stanford.edu, Dimitris Bertsimas,
Nikolaos Trichakis
4 - Risk Tolerance Tempered with Optimal Time Increments
D.J. Alexander-Houle, Adjunct; Program Manager, University of
Phoenix, HP, 14207 Torrey Vista Dr, Houston, TX, 77014,
United States of America, dahoule@sbcglobal.net, G. R. Houle
How people reason about economic choices is risk tolerance.Of social concern is the
risk shift from pooled to personal responsibility. Using the fractal nature of people
creates the framework for risk complexities Grable indicates as, “underlying factor
within Ö decision frameworks” and the aggressiveness of decisions will reflect risk
tolerance levels (2008, p. 4). Research results identifying worst case performance
illustrates a foundation for creating systemic risk tolerance.
In this work, we focus on the problem faced by fund managers when executing
rebalancing trades for multiple accounts simultaneously. We formulate a model that
addresses two key issues, namely how to split the trading costs across the accounts,
and how to incorporate all the information in a scheme for rebalancing the accounts
in a fair way.
2 - Estimating the NIH Efficient Frontier
Dimitrios Bisias, PhD Student, MIT, 70 Pacific Street Apt.327,
Cambridge, MA, 02139, United States of America, dbisias@mit.edu,
Andrew Lo, James Watkins
The National Institutes of Health (NIH) is the preeminent source of funding for
biomedical research, hence its funding allocation decisions have enormous impact
on public health and social welfare. Modern financial portfolio theory is used to
estimate the risk/reward trade-offs of NIH allocation decisions by treating
appropriation as an investment and the decrease in years of life lost as the
investment return.
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WA61
■ WA61
■ WA62
H - Room 400, 4th Floor
Operations Management V
Aviation Applications III
Contributed Session
Contributed Session
Chair: Heping Liu, North Dakota State University, Department of
Industrial & Manufacturing, Fargo, ND, 58108, United States of America,
hepingliu@yahoo.com
1 - Constraint and Flight Rule Management for Space
Mission Operations
John Chachere, Senior Computer Scientist, Stinger Ghaffarian
Technologies, 1060 Arbor Road, Menlo Park, CA, 94025, United
States of America, john.m.chachere@nasa.gov, Jeremy Frank,
Javier Barreiro
Chair: Akira Kondo, Federal Aviation Administration, 800 Independence
Ave., SW, Washington, DC, 20591, United States of America,
akira.kondo@faa.gov
1 - Customer Profitability Analysis for Marketing Initiatives in a
Fractional Airline
Jintao Ouyang, CitationAir, 5 American Lane, Greenwich, CT,
06831, United States of America, jouyang@citationair.com,
Aang Daniel, Roger Zhan, Haiyuan Wang
Due to the operation nature of fractional airlines, operation costs such as charter
premium and position do not directly link to specific customers. A regression based
statistical method is presented to associate these costs to each customer. We also
identify the factors that affect the profitability of customers. These factors can be
used for marketing initiatives such as contract renewal, customer retention, and
devising new pricing schemes.
NASA’s Mission Operations Directorate (MOD) has formalized thousands of
operational constraints to help govern human spaceflight missions. MOD collects,
develops, documents and applies these constraints to ensure the safety of the crew,
as well as proper operation of the spacecraft systems and payloads. These constraints
are stored in human-readable documents and also used to configure tools used by
the flight controllers who plan and fly missions. We have begun developing a novel
capability for authoring and maintaining such constraints called the Constraint and
Flight Rule Management system (ConFRM). ConFRM provides history tracking and
commenting features that allow authors to trace the history of constraints
throughout their lifecycle. ConFRM maintains links between related constraints,
and between constraints and source information used to create the constraints.
ConFRM uses these links to ensure consistency between constraints throughout
their lifecycle, and provides authors and reviewers the ability to navigate between
constraints and related data. Finally, ConFRM enables export of constraints into
many different forms, including human readable documents and tool
configurations, thereby eliminating manual labor and reducing transcription errors.
2 - Optimized Airport Security Study
Shannon Harris, Technomics, Inc, 201 12th Street South, Suite 612,
Arlington, VA, 22202, United States of America,
sharris@technomics.net, Joon Kim, Jaime Gonzalez,
Elizabeth Wilson
The current security measures implemented at airports produce “soft targets” in the
form of lengthy queues that heighten the risk of a terrorist attack. This study
examines Washington Dulles and designs a model to improve the allocation and
usage of security resources. Two alternative designs make use of layered, defense-indepth security measures and the concept of unpredictability. The best alternative is
selected by analyzing simulation outputs based on a value function.
2 - Reverse Ranking and Overshooting in Supply Chains with Private
Inventory Information
Alexandre Belloni, Assistant Professor, Duke University,
1 Towerview Drive, Durham, NC, 27708, United States of America,
abn5@duke.edu, Giuseppe Lopomo, Shouqiang Wang
3 - A Value-based Time-Phased Bayesian Network (VTBN) for
Augmented Safety Risk Assessment
James Luxhoj, Professor, Rutgers University, 96 Frelinghuysen Road,
Dept. of ISE, Piscataway NJ 08854, United States of America, jluxhoj@rci.rutgers.edu, Michael Morton
We study contracts for a single supplier with fixed capacity selling to multiple
retailers who are privately informed on their inventory levels. In symmetric
environments, instead of a balancing policy, it is optimal for the supplier to make
retailers with lower initial inventory levels end up with a larger final positions
(reverse ranking). We characterize when it is optimal to ``overshoot” to provide a
larger quantity to a retailer than it would get in the corresponding centralized
system.
The use of Unmanned Aircraft Systems (UAS) for civil applications is increasing in
the United States. There is a need to develop advanced risk models that capture the
complexities of integrating aviation regulations, functions, hazards and causal factors into a probabilistic model for augmented safety assurance. This presentation
introduces a Bayesian Network that integrates the use of value functions and time
phasing for modeling safety risk analysis of small UAS applications.
3 - Backup Agreements in Multiple Component Procurements with
Demand Updates
Mingchang Wu, PhD Student, University of Connecticut, 2100
Hillside Road, Storrs Mansfield, Storrs Mansfield, CT, 06269, United
States of America, mingchang.wu@business.uconn.edu, Suresh Nair,
Lakshman Thakur
4 - Departure Demand, Efficiency, Taxi-out Delay, and Unimpeded
Taxi-out Time
Akira Kondo, Federal Aviation Administration, 800 Independence
Ave., SW, Washington, DC, 20591, United States of America,
akira.kondo@faa.gov
Taxi-out delays play an important role in the computation of key airport
performance metrics. In this system, departure demand and resulting airport
departure efficiency significantly impact crucial parts in System Airport Efficiency
Rate (SAER). This study provides a new definition of taxi-out times and how
estimation of unimpeded taxi-out time affects computation of taxi-out delays.
We study a supply chain where a manufacturer buys two different components
from two suppliers to produce one product for the selling season.This is an
extension of Eppen and Iyer’s work,where we now look at components rather than
end product.With each supplier,the manufacturer has a particular backup
agreement.Our objective is to derive an optimal purchase policy which describes the
optimal commitments to each supplier and a reaction plan to the demand updates at
the later stage.
■ WA63
4 - The Optimum Policies to the Distribution/Inventory System Problem
in the Medical Center
Jimmy Alexander Carvajal Beltran, Student, Universidad de los
Andes, Carrera 1 N° 18A - 12, Bogotà, Colombia,
ja.carvajal911@uniandes.edu.co, Ciro Alberto Amaya Guio,
Fabiàn Andrés Castaño Giraldo, Nubia Milena Velasco Rodriguez
Decision Analysis For Public Health
Sponsor: Decision Analysis
Sponsored Session
Chair: Ozgur Araz, Postdoctoral Fellow, University of Texas at Austin,
Patterson Lab 628, Austin, TX, 78712, United States of America,
oaraz@mail.utexas.edu
1 - Comparing Cost-effectiveness of Physical Activity Interventions
Shinyi Wu, Assistant Professor, University of Southern California,
3715 McClintock Ave., GER 240C, Los Angeles, CA, 90089,
United States of America, shinyiwu@usc.edu
This paper describes a new approach for solving the budget constrained distribution
and inventory problem for one warehouse and n retailers. This is a typical situation
in medical supply networks where a single warehouse supplies a set of pharmacies
with the main objective of minimizing total costs. To solve the problem, we propose
an iterative algorithm which uses mathematical programming methods. We present
the principal ideas of this approach and results using random instances.
5 - Simulation Modeling for Clinic Telephone Systems
Heping Liu, North Dakota State University, Department of Industrial
& Manufacturing, Fargo, ND, 58108, United States of America,
hepingliu@yahoo.com, Jing Shi
We conducted a systematic review and developed a method to compare costeffectiveness (CE) across a wide variety of physical activity (PA) intervention
strategies. Study quality was variable. Decision prompts were most cost-effective but
had tiny effects. School-based and other wide-reach interventions ranked well. High
intensity programs were least cost-effective but had the largest effect sizes. The CE,
effect size, and study quality should all be considered when choosing PA
interventions.
Clinic telephone systems can guide patients to obtain optimal healthcare delivery
services. In our research, simulation modeling is used to optimize clinic telephone
systems with the functions of leaving messages and call-back services. Centralization
and decentralization are two considered telephone system frames. According to
operator utilization and patient satisfaction level, various scenarios are designed and
simulated. The obtained results can benefit the telephone system configuration.
380
2 - A Decision Analytic Approach for Modeling School Closures During
an Influenza Pandemic
Ozgur Araz, Postdoctoral Fellow, University of Texas at Austin,
Patterson Lab 628, Austin, TX, 78712, United States of America,
oaraz@mail.utexas.edu, Sean Burke, Paul Damien, Lauren Meyers,
Bryce van de Geijn, Alison Galvani
WA65
5 - Workload Scoring of Nurse to Patient Assignments
Ilgin Acar, Anadolu University, Department Of Industrial
Engineering, Iki Eylul Campus, Eskisehir, 26555, Turkey,
ipoyraz@anadolu.edu.tr, Steven Butt
This work is the first to explicitly consider incorporating travel distances into the
construction of a nurse’s patient assignments through the construction of a
workload score based on nurse travel distances and patient acuity measures. The
workload scores were developed through consultation with charge nurses using
AHP. The resulting tool displays a nurse’s assigned rooms and associated workload
score in an accessible spreadsheet format.
In this presentation, we present a decision analytic approach for making school
closure decisions during an influenza pandemic. We build a mass action model and
assume the severity of the disease is uncertain for the decision makers. A decision
tree is used to evaluate several closure and reopening decisions simultaneously
based on their cost effectiveness. Lastly, we perform several sensitivity analyses on
decision making parameters and present our results.
■ WA65
3 - Dynamics of a Pharmaceutical Risk Sharing Agreement
Reza Mahjoub, PhD Student, Ivey Business School, 1151 Richmond
St., London, ON, Canada, rmahjoub@ivey.uwo.ca, Fredrik Odegaard,
Greg Zaric
Inventory Management V
Contributed Session
Some new drugs such as cancer drugs could be very costly to develop and
manufacture while their effectiveness and efficiency in real life may be unproven. A
risk sharing agreement is a contract between the drug manufacturer and a
healthcare payer to manage uncertainties regarding the cost and effectiveness of
those drugs. We develop a model to examine the dynamics of a risk sharing contract
for a drug manufacturer.
Chair: Ayse Gönül Karaarslan, PhD Candidate, Eindhoven University of
Technology, P.O. Box 513, Eindhoven, 5600 MB, Netherlands,
a.g.karaarslan@tue.nl
1 - A Simulation-optimization Approach to the Inventory Mangement of
Perishable and Substitutable Items
Bret Myers, Villanova University, 442 Hartford Square, West Chester,
PA, 19380, United States of America, bret.myers@villanova.edu
■ WA64
A simulation-optimization approach is used to analyze inventory policy for two
perishable and substitutable items. A set of perishable items is considered under a
periodic system of inventory control where demand for a preferred item can be
satisfied by a substitute item with in the event of a stockout of the preferred item.
The retailer is faced with the decision of determining the order-up-to levels which
maximize expected total profit.
Health Care, Modeling and Optimization V
Contributed Session
Chair: Ilgin Acar, Anadolu University, Department Of Industrial
Engineering, Iki Eylul Campus, Eskisehir, 26555, Turkey,
ipoyraz@anadolu.edu.tr
1 - Consensus by Averaging Phylogenetic Trees
Scott Provan, University North Carolina, Department Statistics and
Operations Research, Chapel Hill, NC, 27599, United States of
America, Scott_Provan@UNC.edu, Ezra Miller, Megan Owen
2 - Policy Parameter Adjustments to Meet Desired Service Level
Requirements for (r, NQ) Inventory Models
Yasin Unlu, University of Arkansas, 4207 Bell Engineering Center,
Fayetteville, AR, 72701, United States of America, yunlu@uark.edu,
Manuel D Rossetti
This study introduces a simulation optimization based procedure for setting policy
parameters of continuous review (r, NQ) inventory models in the face of complex
demand cases. The experiments done with various demand scenarios show that the
procedure yields promising results in terms of attaining specified target service
levels.
We introduce a new notion of the consensus tree for a set of phylogenetic trees, by
representing them as points in the phylogenetic tree space of Billera, Holmes, and
Vogtmann. The property of non-positive curvature of this space ensures that the
consensus tree captures the correct notion of an “average” tree, and that there is an
algorithm for computing this tree. We give as applications reconstructing species
trees from gene trees and comparing the structure of blood vessels in the brain.
3 - A Multiple-level Supply Chain Coordination Model by (Q, r) Policies
in a Fuzzy Environment
Xinmin Wu, OR Specialist, SAS, Sas Campus Drive, Cary, 27513,
United States of America, xinmin.wu@sas.com, Don Warsing
2 - A Probabilistic Optimization Approach to Analyze Large Scale
Emergency Medical System on Highways
Ana Iannoni, Ecole Centrale Paris - Laboratoire Genie Industriel,
Grande Voie des Vignes, Chatenay Malabry, 92295, France,
iannoni93@hotmail.com, Reinaldo Morabito, Cem Saydam
we present a serial multiple-level supply chain coordination model by (Q,r) policies
in a fuzzy risk environment. Sources of risk and uncertainty in our model include
demand, lead time, supplier yield, which are modeled by fuzzy sets. Heuristics are
presented to determine local optimal policies on the basis of techniques identified in
the literature on fuzzy sets. A coordination process with an external coordinator is
implemented to improve supply chain performance based on global view.
In this study we present optimization methods based on greedy heuristics
embedding an approximate hypercube queuing model. The proposed approach can
support two decisions in the operation of emergency systems on highways: the
location and districting of the ambulances. We applied these methods to a case study
and to instances of up to 100 ambulances. The present approach is an alternative for
the analysis of large scale systems, which provides reasonable accuracy and
affordable running times.
4 - A Modified Base Stock Policy for an Assemble to Order System
with Different Review Periods
Ayse Gönül Karaarslan, PhD Candidate, Eindhoven University of
a.g.karaarslan@tue.nl, Ton de Kok, Gudrun P. Kiesmüller
3 - A Multi-class Open Queuing Network with Priority Discipline
Applied to the Emergency Department
Sumi Kim, Yonsei University, Shinchon-dong, Seodaemun-gu, Seoul,
Korea, Republic of, sumi_kim@yonsei.ac.kr, Seongmoon Kim
We have a single item assembled from two components. The inventory levels are
reviewed periodically and customer demand is stochastic. One of the components
has a longer lead time, higher holding cost and shorter review period compared to
the other one. We analyze a modified base stock policy such that one stockpoint is
controlled by an order-up to policy. The orders for the other stockpoint are
synchronized depending on its order-up-to level and the inventory level of the
other component.
We formulate the patient flows in the emergency department using a multi-class
open queueing network. The unique aspect of this paper is that it incorporates the
priority discipline with the queueing network, in order to control the waiting time
of more urgent patients. A case study based on actual data from an emergency
department demonstrates how effective the introduced model and the policy with
the priority discipline are in controlling the waiting time and improving the quality
of service.
4 - Optimal Clinical Scheduling with No-shows
Ji Lin, PhD Candidate, Purdue University, Weldon School of
Biomedical Engineering, 206 S. Martin Jischke Drive, West Lafayette,
IN, 47907, United States of America, lin35@purdue.edu,
Mark Lawley, Kumar Muthuraman
The accessibility and efficiency of outpatient care are largely affected by the
appointment schedules. Patient no-show causes waste of physician time and
revenue loss. Random booking results in long waiting time and overtime. Patients
usually have different no-show rates. Thus, we propose MDP model and optimal
scheduling policies for heterogeneous no-show patients. Approximate Dynamic
Programming methods are developed to solve the curse of dimensionality.
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2 - Modeling Parameter Uncertainty in Stochastic Simulations
Canan Gunes, PhD Student, Carnegie Mellon University, 5000
Forbes Avenue, Pittsburgh, PA, 15213, United States of America,
cgunes@andrew.cmu.edu, Bahar Biller
Transportation, Other
We consider a stochastic simulation and demonstrate how to account for stochastic
uncertainty and parameter uncertainty in the output analysis. We further
decompose the variance of the output data into terms associated with each type of
uncertainty and use this decomposition to develop a data-collection schema for
reducing parameter uncertainty. We illustrate our approach with inventory system
simulations.
Contributed Session
Chair: Gokhan Memisoglu, PhD Student, Texas A&M University,
Department of Industrial and Systems Eng, Texas A&M University,
College Station, TX, 77843-3131, United States of America,
gmemis@tamu.edu
1 - A Net Present Value Model for Investment in Airport Assets
Alexandre de Carvalho, Instituto de Pesquisa EconÙmica Aplicada IPEA, Diretoria de Estudos Regionais e Urbanos, SBS Quadra 1,
Edificio BNDES, sala 718, Brasilia, DF, 70076-900, Brazil,
alexandre.ywata@ipea.gov.br, Alessandro VM de Oliveira,
Reinaldo C. Garcia
3 - A Discrete Simulation Approach to the Design of a Warehouse for
Air Cargo Operations
Carlos Osorio, Politecnico Grancolombiano, Calle 57 3-00 Este Fac
Ingenieria, Bogota, Colombia, caosorio@poli.edu.co,
Oscar Javier Parra Ortega
This paper shows the application of discrete simulation for designing the main air
cargo warehouse of one of the biggest airlines in Colombia and South America. The
research begins with the evaluation of the operations carried out in the warehouse;
the current performance is analyzed using key logistics indicators, and prospective
scenarios are then generated and evaluated. Preeliminary results are also reported.
Improvement and expansion in infrastructure transport assets are among the main
concerns facing the transport specialists due to the high investments involved. The
timing and the combination of new transport investments is key to analyze their
long-term effects. This paper proposes an investment model based on Net Present
Value (NPV) analysis. In particular, the model is applied to: (i) the building of a new
airport; and (ii) the expansion of already existing “major” and “minor” airports.
4 - Simulation to Identify Errors in Generalized Tournaments
Christopher Keller, Assistant Professor of Marketing and Supply
School of Business, Greenville, NC, 27858, United States of America,
kellerc@ecu.edu
2 - Network Connectivity Analysis for Port Competitiveness Study
Ek Peng Chew, Associate Professor, National University of Singapore,
10 Kent Ridge Crescent, Singapore, 669606, Singapore,
isecep@nus.edu.sg, Loo Hay Lee, Jianlin Jiang, Chee Chun Gan
This paper presents a Monte Carlo simulation of ranking participants in a
generalized tournament, including variations in: number of participants;
completeness of the tournament; and paired comparison errors. Some paired
comparison errors are not reliably identifiable and a complete and accurate ordering
of participants is unlikely. Using a partial ordering topological rank, jackknife
estimates of the average rank do admit the identification of some of the paired
comparison errors.
Port connectivity is an important factor that deserves much attention in the study of
port competitiveness. Determining how well one port connects to others is hardly
easy, as it being an abstract concept might bring about different interpretations and
definitions in different cases. In this paper, we will propose a measure using
network anaylsis to measure port connectivity.
3 - Student Assignment Models for a School System
Trivikram Rao, PhD Student, University of Louisville, Department of
Industrial Engineering, JB Speed School of Engineering, Louisville,
KY, 40292, United States of America, trivikram.rao@louisville.edu,
Arsalan Paleshi, Bulent Erenay
5 - Simulating Social Networks in Understanding Dynamics of
Customer Purchase Behavior: Case of Cult Brands
Ahmet Ozkul, Assistant Professor of Management, University of New
Haven, 300 Boston Post Rd., Maxcy Hall, West Haven, CT, 06516,
United States of America, aozkul@newhaven.edu, Aqin Hu
This research proposes a mathematical programming approach for student
assignment to schools while incorporating quantitative, qualitative constraints such
as travel cost, parental preferences, and socio-economic constraints. The model’s
sensitivity in cost, parental satisfaction terms to certain constraints is tested. Also,
extension of this approach to other assignment problems is discussed.
When we consider customers as actors in a purchasing relationship of products,
Social Network Analysis may be used to reveal unknown patterns and explain
customer behavior. Using a simulation analysis, we create a market of M customers
and N products. Customers create a relationship when they buy a given product.
The number of links and frequency of the purchase determine the nature of the
relationship. We calculate social network measures in each cycle to observe the
dynamics.
4 - Optimal Deployment of Emissions Reduction Technologies for
Large Fleets
Gokhan Memisoglu, PhD Student, Texas A&M University,
Department of Industrial and Systems Eng, Texas A&M University,
College Station, TX, 77843-3131, United States of America,
gmemis@tamu.edu, Mohamadreza Farzaneh, Kiavash Kianfar
■ WA68
In states that have serious air quality problems, such as Texas and California, public
fleet managers are under pressure to reduce emissions from their fleet. In order to
help them with this problem, this research study will create an optimization model
capable of determining the most efficient assignment of emission reduction
strategies among vehicles and equipment in a large fleet. To achieve the goal, this
study will focus on Texas Department of Transportation’s (TxDOT’s) fleet.
Innovation/Entrepreneurship I
Contributed Session
Chair: Arash Dadvand, CGN and Associates, 415 SW Washington St,
Peoria, IL, 61602, United States of America, adadvand@cgn.net
1 - Diffusion of Innovation Products: Network Effects and
Bandwagon Effects
Shuzhen Sun, School of Industrial Engineering & Management,
Oklahoma State University, School of Industrial Engineering & Mgt.,
Oklahoma State University, Stillwater, Ok, 74078,
United States of America, zhener18@gmail.com, Di Xu
■ WA67
Simulation I
Contributed Session
Bandwagon effects and network effects play important roles in consumers’ purchase
decisions. This paper uses the small-world network model to study the two effects
on the diffusion of innovation products. Simulations are conducted to examine the
diffusion process and adoption rate under different levels of bandwagon pressures,
different strength of network effects,and different network configurations, on the
assumption that bandwagon effects exist in all conditions.
Chair: Ahmet Ozkul, Assistant Professor of Management, University of
New Haven, 300 Boston Post Rd., Maxcy Hall, West Haven, CT, 06516,
United States of America, aozkul@newhaven.edu
1 - Incorporating Analytic Hierarchy Process with Simulation to Assess
Health Service Quality
Yan Li, The University of Texas-Pan American, 508 E Redbud Ave,
Mcallen, TX, 78504, United States of America,
tongjijacky@hotmail.com, Jianzhi Li
2 - A System Dynamics Model to Understand Innovation in the
Design Process
Nur Ozge Ozaltin, University of Pittsburgh, 1048 Benedum Hall,
Pittsburgh, PA, 15261, United States of America, noo7@pitt.edu,
Mary Besterfield-Sacre, Larry Shuman
While improving quality in health care is currently at the forefront of professional,
political, and managerial attention, it has yet to fully understand the key dimensions
constituting health-care quality and develop valid approaches to their measurement.
The methodology proposed in this paper, AHP based simulation, will provide great
insights in tackling this problem and open up a world of possibilities for future
research.
To improve innovation, it should be better understood how the teams navigate the
design process from initial conception to prototype. We examine the bioengineering
design process to investigate associations between design patterns and the quality of
the resulting artifact. We identify the critical patterns and factors that lead to
innovation.
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3 - Entrepreneurship and Community Development: A Fallacy From
Central Mexico
Eliseo Vilalta-Perdomo, Head Dept Industrial and Systems
Engineering, Tecnológico de Monterrey, Av Gral Ramón Corona
2514, Col. Nuevo México, Zapopan, 45201, Mexico,
eliseo.vilalta@itesm.mx, Cynthia Montaudon-Tomas
H - Salon G, 6th Floor
Planning and Strategies for Airline Operations
Sponsor: Aviation Applications
Sponsored Session
To consider entrepreneurship as a dynamo for economic development is challenged
throughout this work done in central Mexico. Two programs from different rural
communities in Guanajuato are studied. Probably the most promising finding is to
recognize that individual economic development and community social
development are not linked. A proposal to increase quality of life in rural
communities is presented. It is centered on creating and maintaining self-organized
web-based networks.
Chair: Sergey Shebalov, Principal Research Analyst, Sabre Holdings,
Dallas/Fort Worth, TX, United States of America,
Sergey.Shebalov@sabre-holdings.com
1 - Baggage Capacity and Demand Management Becomes Even
More Sophisticated
Desmond Di Wang, Northwestern University, 2145 Sheridan Road,
Evanston, IL, 60208, United States of America,
diwang2007@u.northwestern.edu, Diego Klabjan
4 - Efficient Targeted Concept Development Method
Arash Dadvand, CGN and Associates, 415 SW Washington St, Peoria,
IL, 61602, United States of America, adadvand@cgn.net
While sophisticated forecasting management systems exist for the passengers and
cargo load of an aircraft, this is not the case for baggage despite significant costs
associate with baggage mishandling. It is thus desirable to detect excessive baggage
load early during the booking process to avoid dire consequences for both
passengers and the airline. We present methodologies behind a system for baggage
load forecasting any number of days before the day of operations.
Breakthrough competitive advantage are accomplished by competitive concepts.
Concept development is costly, hard to manage and may not result in a viable
solution. This is a method to formulate a problem, effectively and efficiently create
concepts based on generic cross-industry patented solutions, and prioritize concepts
to meet predefined goals. Final set of concepts could be optimized and improved.
2 - Short-term Maintenance Allocation
Sergey Shebalov, Principal Research Analyst, Sabre Holdings,
Dallas/Fort Worth, TX, United States of America,
Sergey.Shebalov@sabre-holdings.com
■ WA69
H - Salon F, 6th Floor
Short-term maintenance allocation involves building and supporting maintenance
schedule for each tail to ensure its operationability. We present a model that creates
an optimal set of maintenance blocks for a given tail assignment and allocates
maintenance events to them. We optimize aircraft utilization and maintenance cost
while maintenance capacity is constrained. We extend our formulation to allow
overnight aircraft swaps and thus integrate maintenance allocation and tail
assignment.
Transportation, Rail
Contributed Session
Chair: Katharina Beygang, University of Kaiserslautern, Department of
Mathematics, OR Group, Postfach 3049, Kaiserslautern, 67653, Germany,
beygang@mathematik.uni-kl.de
1 - Extensions to the Online Delay Management Problem on a
Single Train Line
Christiane Zeck, University of Kaiserslautern, Department of
Mathematics, OR Group, Postfach 3049, Kaiserslautern, 67653,
Germany, zeck@mathematik.uni-kl.de, Sven O. Krumke,
Clemens Thielen
3 - Planeside Manpower Planning at United Airlines
Feryal Kuran, United Airlines, 1200 E. Algonquin Rd., Elk Grove
Village, IL, United States of America, Feryal.Kuran@united.com,
Kumar Satyam
Planeside Tool is a major component of the Ramp Operations automation strategy at
United Airlines. Initial phase enables manual assignment of resources to cover
arrival and departure packages. Model, developed by Enterprise Optimization,
suggests best assignment of resources to packages and lunches over multiple hours
considering various factors. Weighting of factors can be adjusted depending on
needs of operations. Model enables improved coverage of flights and better
utilization of resources.
The online delay management problem consists in deciding when to wait for
delayed passengers in order to minimize the total passenger delay. Viewing this
problem in the context of game theory, we determine an optimal online strategy.
We also introduce a new objective function modeling a refund system for delayed
passengers with the aim of maximizing the profit. For this problem, there cannot be
a competitive deterministic online algorithm, but we present a 2-competitive
randomized algorithm.
4 - Structured Deplaning: A Simulation and Optimization of
Implementable Strategies
Andrew Wald, Northwestern University, 2145 Sheridan Road,
andrewwald@gmx.com, Diego Klabjan
2 - Railway Routing Algorithms for Hazardous Materials
Marc Meketon, Oliver Wyman, 212 Carnegie Center, Princeton, NJ,
08540, United States of America, Marc.Meketon@oliverwyman.com,
Paul Stephens
Deplaning naturally occurs row by row down the length of an aircraft. Using
simulation and optimization, we design deplaning strategies (e.g., deplane by group)
that significantly reduce the overall deplaning time. These evaluations are
established through field observations and simulation, and have been tested across
several equipment types.
New Federal Railroad Administration guidelines require examining various
hazardous material routing alternatives. The shortest path may traverse large
population centers or other non-desirable areas. Finding a set of acceptable paths is
challenging for large railroads where the “K-shortest” paths differ insignificantly.
This research discusses solutions to the important, but difficult, task of identifying
different paths with acceptable distance and cost that also represent real
alternatives.
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3 - Efficient Usage of Railway Infrastructure Through
Pricing Mechanisms
Arnt-Gunnar Lium, Research Scientist, SINTEF Technology and
Society, P.O. Box 4760 Sluppen, Trondheim, N 7465, Norway,
arnt-gunnar.lium@sintef.no, Adrian Werner
H - Salon H, 6th Floor
Resource Efficiency and Distribution Models in DEA
Cluster: In Honor of Bill Cooper
Invited Session
Railroad infrastructure is very costly to develop; hence, increased utilization will
have a significant positive impact on society. One way of increasing utilization over
the day is to implement tariffs such that railroad operators adapt their schedules in a
socio-economical optimal way. We look into how bi-level programming can be
combined with stochastic service network design to determine socio-economical
optimal tariffs.
Chair: Subhash Ray, University of Connecticut, CT, United States of
America, subhash.ray@uconn.edu
1 - Using DEA to Help the Regulator Set Promulgated Insurance Rates
Patrick Brockett, University of Texas, TX, United States of America,
brockett@mail.utexas.edu, William Cooper, Jing Ai, Charles Yang,
Linda Golden, Utai Pitaktong
4 - Extensions to the Train Marshalling Problem
Katharina Beygang, University of Kaiserslautern, Department of
Mathematics, OR Group, Postfach 3049, Kaiserslautern, 67653,
Germany, beygang@mathematik.uni-kl.de, Sven O. Krumke
We offer a methodology for setting efficient promulgated insurance rates illustrated
through an application to title insurance rate setting. In title insurance, losses
constitute a tiny percentage of the premium, and expenses dominate the rates.
Rates are set (in Texas) by the regulator relying upon average expenses and loss
ratios. This inflates rates and rewards inefficiency, since inefficient agents with
higher expenses drive up the average expense resulting in higher promulgated rates.
We use DEA to: identify those title agents that efficiently utilize their resources to
produce policies, and show how rates can be promulgated based upon the expenses
of only these efficient agents, thus encouraging efficient management and
reasonable rates.
Shunting yards, consisting of a hump and a set of parallel classification tracks, play
an important role in railroad life. They are used for the rearrangement of cars
according to their destinations. The Train Marshalling Problem consists of
minimizing the number of classification tracks needed for the rearrangement of a
given car sequence. It is well known to be NP-complete. We give competitive
polynomial time algorithms for the online variant as well as lower bounds on the
competitiveness.
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2 - A DEA Approach to Simulation Output Analysis of an Agent-based
Model of a Distribution Network
William Sawaya, Assistant Professor, Texas A&M University, Eng.
Tech. and Industrial Distribution, College Station, TX, 77845,
United States of America, sawaya@tamu.edu, Andrew Johnson, Sri
Nagendra Jayanty
H - Salon K, 6th Floor
Supply Chain: Reverse Logistics, Cost of Quality
Sponsor: Transportation Science and Logistics Society
Sponsored Session
Simulation output analysis for comparing different systems configurations can be
complicated by the fact that there are often multiple performance variables of
interest. This complexity can be further compounded in agent-based system because
it is conceivable that there are multiple agents that each have their own
performance information. This research presents a DEA approach analyzing
simulation output of different system configurations for multiple organizations in a
distribution network.
Chair: Theresa Barker, PhD, University of Washington, Box 352650,
Seattle, WA, 98115, United States of America,
barkertj@u.washington.edu
1 - Cost Sharing for Economic Lot-Sizing Problems with
Remanufacturing Options
Mohan Gopaladesikan, School of Industrial Engineering, Purdue
University, 315 N. Grant Street, Grissom Hall 308, West Lafayette,
IN, 47907, United States of America, mohang@purdue.edu,
Nelson Uhan
3 - Cost Efficiency in a Model of Production and Distribution
Subhash Ray, University of Connecticut, CT, United States of
America, subhash.ray@uconn.edu
This paper develops a measure of overall cost efficiency in an integrated model of
production and distribution. The DEA model introduced by Ray et al (2008) for
multi-location cost minimization in the presence of input price variation across
locations is combined with the standard transportation model. The principal
innovation is that optimal quantities produced at different locations and the
quantities shipped to different destinations are determined simultaneously in a
unified DEA model that minimizes total production and distribution cost.
We consider a class of cooperative games that model the cost sharing issues that
arise from the economic lot-sizing problem with remanufacturing options. By
investigating the properties of various mathematical programming formulations and
relaxations for the underlying lot-sizing problem, we obtain some insights into the
existence of cost allocations in the core and the approximate core of these games, as
well as the algorithmic aspects of computing such cost allocations.
2 - Robust Design of Computer Remanufacturing and
Recycling Facilities
Suzanne Marcotte, Professor, Universite du Quebec a Montreal,
315 rue Ste-Catherine Est, Montreal, QC, H2X 3X2, Canada,
Suzanne.Marcotte@cirrelt.ca, Benoit Montreuil
■ WA72
H - Salon J, 6th Floor
This presentation will describe the capacity planning of resources required in a
computer remanufacturing and recycling facility. It will describe the generic process
and the operations and decisions to be taken. Each operation of this process is
characterized by sources of uncertainty and variability. It will then present results
on the capacity required given various level of uncertainty.
Joint Session TSL/ SPPSN: Aiding Disaster Relief
Through Optimization
Sponsor: Transportation Science and Logistics Society/ Public
Programs, Service and Needs
Sponsored Session
3 - Integrating Cost of Quality in Supply Chain Modeling:
A Preliminary Study
Krystel K. Castillo-Villar, Texas Tech University-Tecnologico de
Monterrey, Box 43061, Lubbock, TX, 79409-3061,
United States of America, krystel.castillo@ttu.edu, Neale R. Smith,
James L. Simonton
Chair: Irina Dolinskaya, Assistant Professor, Northwestern University,
2145 Sheridan Road, M235, Evanston, IL, 60208, United States of
America, dolira@northwestern.edu
1 - Continuous Approximations for Relief Routing
Michael Huang, Northwestern University, 2145 Sheridan Rd,
Evanston, IL, 60208, United States of America, MichaelHuang@u.northwestern.edu, Karen Smilowitz
This work presents a preliminary methodology to compute the cost incurred by
various actors within the supply chain due to the cost of poor quality or cost of
quality (CoQ). We consider a generic consumer goods supply chain, consisting of
three tiers, namely suppliers, manufacturers, and retailers. The purpose of this work
is to provide a guide to translate defect rates at supplier, manufacturing plant, and
retailer to quality costs. The study recommends ways quality engineers can use the
methodology to make decisions regarding investment in prevention activities,
rework process, inspection, among others. The practical implications of this research
are a better selection of suppliers and manufacturing plants based on quality and
cost considerations and a better understanding of CoQ not just as an internal, but
also as an external performance measure. The study offers insights based on the
findings and provides guidelines for future research.
In relief routing, solutions must be found quickly and should be easy to implement.
We describe a simple policy and develop analytic approximations to measure its
effectiveness. We demonstrate the accuracy of the approximations’ by comparing
the predicted values against simulations of the policy. Finally, we test the solutions
from the policy against more sophisticated polices generated with a Tabu search.
2 - A Review on Recent OR Research in Disaster
Operations Management
Rajan Batta, Professor and Associate Dean, University at Buffalo
(SUNY), Department of Industrial & Systems Engg, 438 Bell Hall,
Buffalo, NY, 14260, United States of America, batta@buffalo.edu,
Gina Galindo
■ WA74
Disasters have attracted the attention of OR researches who are interested on
applying scientific techniques to improve DOM effectiveness, and reduce the
consequences of disasters on the economy and human lives. In this talk a review on
recent OR research in DOM is offered and some future research directions are
proposed.
Optimal Sensor Location and Deployment
Sponsored Session
3 - Modeling Disaster Relief Networks
Luis de la Torre, PhD Candidate, Northwestern University, 2145
Sheridan Road, IEMS, Tech C210, Evanston, IL, 60201, United States
of America, ledelatorre@u.northwestern.edu, Irina Dolinskaya,
Karen Smilowitz
Chair: Yi-Chang Chiu, University of Arizona, Tucson, AZ,
United States of America, chiu@email.arizona.edu
1 - Permanent Traffic Counter Location Problem on
Transportation Network
Fatemeh Sayyady, Research Assistant, North Carolina State
University, 2501 Stinson Drive, 208 Mann Hall, Raleigh, NC, 27695,
United States of America, fsayyad@ncsu.edu, George List,
Yahya Fathi, John Stone
This talk presents our research in last mile operations of disaster relief distribution.
In particular, we focus on how distribution problems are represented in operations
research models and characteristics of distribution in practice. We discuss
implications of problem assumptions in both modeling and implementation.
We consider the problem of determining an optimal placement for the traffic
counters on a large-scale highway network, subject to a budget constraint. We
formulate the problem as a mixed integer linear programming problem, and show
that it has structural similarities with the p-median problem as well as the knapsack
problem. A reasonably fast Lagrangian-heuristic approach is presented to solve large
size instances of the problem where CPLEX fails to report optimal values.
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2 - Traffic Sensor Deployment Under Probabilistic Disruptions and
Generalized Surveillance Effectiveness Measures
Xiaopeng Li, University of Illinois at Urbana-Champaign, B156
Newmark Civil Engineering Laborator, 205 N. Mathews Ave,
Urbana, IL, 61821, United States of America, li28@illinois.edu,
Yanfeng Ouyang
WB02
4 - Scenario Reduction Methods for Rolling Stochastic Energy
Planning Programs
Yan Wang, PhD Student, Iowa State University, 3004 Black
Engineering, Ames, IA, 50010, United States of America,
yanwang@iastate.edu, Sarah Ryan
A medium-term fuel procurement and electricity generation planning problem is
naturally solved as a rolling horizon series of stochastic programs with evolving fuel
price forecasts. We examine the accuracy and computational efficiency of a scenario
reduction heuristic that emphasizes the initial decision rather than the distribution
of scenarios.
We propose a reliable sensor location model to optimize surveillance effectiveness
when sensors are subject to site-dependent probabilistic failures, and a general
effectiveness measure is proposed to encompass most existing measures needed for
engineering practice. We formulate a compact mixed-integer program and develop a
variety of solution algorithms. We also propose alternative formulations in the form
of reliable fixed-charge sensor location models.
■ WB02
3 - A Continuum Approximation Approach to Reliable Traffic Sensor
Deployment on Highway Corridors
Xiaopeng Li, University of Illinois at Urbana-Champaign, B156
Newmark Civil Engineering Laborator, 205 N. Mathews Ave,
Urbana, IL, 61821, United States of America, li28@illinois.edu,
Yanfeng Ouyang
Risk Management & Stochastic Programming in
Gas and Power Systems
Cluster: Energy: Modeling the Interface Between Markets
and Operations
Invited Session
We propose a continuum approximation framework for the reliable deployment of
traffic sensors to optimize surveillance effectiveness when sensors are subject to sitedependent probabilistic failures.
Chair: Qipeng Phil Zheng, Assistant Professor, West Virginia University,
Industrial & Management Systems Eng, P.O. Box 6070, Morgantown, WV,
26505, United States of America, Qipeng.Zheng@mail.wvu.edu
1 - Forecasting PHEV Sales and Recharging Activities
Lizhi Wang, Iowa State University, 3016 Black Engineering, Ames,
IA, 50014, United States of America, lzwang@iastate.edu,
Zhaoyang Duan, Brittni Gutierr
4 - Optimal Advance Detector Location for Green Termination Systems
on High Speed Isolated Intersections
Lili Du, NEXTRANS Center, Purdue University, 2700 Kent Avenue,
West Lafayette, IN, 47906, United States of America,
ldu@purdue.edu, Anuj Sharma, Srinivas Peeta
This model finds near-optimum solutions very efficiently, and results from the
approximation method are shown to be very close to those from the discrete
methods.
Sales of plug-in hybrid electric vehicles (PHEVs) and PHEV users recharging
behavior are two critical factors for studying the potential impact of PHEVs on
electric power systems. We present novel approaches to making more accurate and
revealing forecasts of these factors. We will forecast the sales of PHEVs as a function
of several interacting sub-factors, and forecast PHEV users’ recharging behavior as a
function of available recharging infrastructures.
Wednesday, 11:00am - 12:30pm
2 - Identification and Prevention for Blackout on Large-scale
Power Grid
Hongsheng Xu, University of Florida, 303 Weil Hall, P.O. Box
116595, Gainesville, FL, 32611, United States of America,
xuhongsh@ufl.edu
■ WB01
Planning for Uncertainty in Energy Systems
Sponsored Session
A blackout is the situation where there is a total loss of power to a relatively wide
area, and how to quickly identify it in the power grid is key to preventing it from
cascading. In this paper, we are focusing on detecting the possible blackout using
our proposed evaluation criteria and algorithms. The results above could lead to
some strategy guidance for designing and operation power grid. A computational
study is presented in which we apply our model to the simulated data sets.
Chair: Sarah Ryan, Professor, Iowa State University, 3004 Black
Engineering Bldg., Ames, IA, 50011-2164, United States of America,
smryan@iastate.edu
1 - Electric Power System Generation Expansion Planning Problems
Considering Risk
David Coit, Associate Professor, Rutgers University, Industrial &
Systems Engineering, 96 Frelinghuysen Rd., Piscataway, NJ, 08854,
United States of America, coit@rutgers.edu, Hatice Tekiner,
Frank Felder
3 - Midterm Coordination of Natural Gas Storage and
Power Generation
Cong Liu, Postdoctor, Argonne national Laboratory, 9700 S. Cass
Ave., Bldg 221, Argonne, IL, 60439, United States of America,
liuc@anl.gov, Jianhui Wang, Mohammad Shahidehpour, Zuyi Li
GEP problems are solved to determine generation options to add and where/when
to be constructed considering risk. In studies, decision makers are risk neutral; but
often they are risk averse. We solve a multiobjective optimization problem to
minimize cost and risk. We define a subset of scenarios to represent the stochastic
nature. Multiobjective optimization problem is solved to find a Pareto Front.
In this talk, we will investigate the midterm coordination of natural gas resources
and power generation. The objective is to minimize the integrated social cost
including cost of power and natural gas systems while satisfying their complex
coupled network constraints. The original problem will be decomposed into subproblems for each week. Lagrangian relaxation will be used to relax weekly
coupling constrains of gas storage reservoirs.
2 - Generation Expansion Portfolio Optimization with Stochastic
Production Tax Credit for Wind Power
Jo Min, Iowa State University, IMSE Department, 3004 Black,
Ames, IA, 50011, United States of America, jomin@iastate.edu,
Jin Lee, Chenlu Lou, Chung-Hsiao Wang
4 - Expansion Planning Models for Combined Electricity and
Natural Gas Systems
Alexey Sorokin, University of Florida, 303 Weil Hall, P.O. Box
116595, Gainesville, FL, United States of America, sorokin@ufl.edu,
Vladimir Boginski, Qipeng Phil Zheng
We construct and analyze a generation expansion portfolio model consisting of
conventional power plants and windmills. Specifically, a mean - variance utility
function is optimized under the assumption that the fuel price, electricity price, and
production tax credit for wind power are random variables. Via parametric quadratic
programming, we analytically derive various managerial insights with respect to the
degrees of risk aversion, renewable portfolio standards, and production capacities.
Natural gas is playing an increasingly important role in global energy market
because of its environment friendly properties, especially for electricity generation.
We consider transmission expansion problem for gas and electricity networks, as
well as for LNG terminal location planning. The multiple stage expansion model is
proposed.
3 - Computational Issues in Solving Large-Scale Stochastic Grid
Expansion Problems
Jean-Paul Watson, Sandia National Laboratories,
jwatson@sandia.gov, David Woodruff
Grid generation and transmission expansion problems are frequently expressed as
stochastic mixed-integer programs, commonly multi-stage due to long-term
planning horizons. However, these models are very difficult to solve, due to multiple
exogenous uncertainty sources and scenario tree depth. We investigate the issue of
decomposition solver performance on such problems, focusing on Progressive
Hedging. Computational results and solution strategies are reported for several test
problems.
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WB03
■ WB03
2 - Selection of Talents Based on Decision Making Theory
Shaikh Akhlaque-E-Rasul, Concordia University, 1515 St. Catherine
West, Montreal, Canada, akhlaque1045@hotmail.com,
Sudhir P. Mudur
Environmental Legislation, Carbon Trading and Supply
Chain Management
It is always a difficult task to select the best candidate from many. Sometimes,
biased opinions may skew the selection process. To overcome any bias and to rank
the candidates, we show how decision makers can apply the decision-making
theory of material science, which was developed by D. H. Jee. In the present work,
several case studies from our daily life that benefit from the use of this theory are
presented.
Sponsor: Energy, Natural Resources and the Environment//Forestry
Sponsored Session
Chair: Eda Kemahlioglu-Ziya, University of North Carolina-Chapel Hill,
CB#3490, Chapel Hill, NC, United States of America,
Eda_KemahliogluZiya@unc.edu
1 - Strategic Carbon Footprint Labeling in a Supply Chain
Rob Zuidwijk, Rotterdam School of Management, P.O. Box 1738,
Rotterdam, Netherlands, RZuidwijk@rsm.nl, Charles Corbett,
Chien-Ming Chen
3 - Inclusion of Preference-Dependence in Multi-attribute
Utility Theory (MAUT)
Johannes Siebert, Akademischer Rat, University of Bayreuth,
Lehrstuhl Prof. Schluechtermann, Universitaetsstr. 30, Bayreuth,
95440, Germany, Johannes.Siebert@uni-bayreuth.de
Decision makers express preferences -here considered as factors- as ratios to
averages of the alternative. A Taylor expansion of the product of these factors yields
first and higher order terms. The former depend on each one preference only
whereas the later depend on two or more preferences and are used to model
dependencies. The new model is termed aggregate utility factor model (AUFM). In a
computer-based experiment practicability and consistence in decision making are
confirmed.
When firms plan to put carbon footprint labels on their products, it is often not
unambiguous how those carbon footprints should be determined. Current standards
for carbon footprint reporting also leave room for ambiguity. This gives firms some
flexibility in how to allocate carbon emissions to different products. In this paper,
we examine conditions under which that flexibility in fact helps to reduce the firm’s
total carbon footprint without compromising profits.
2 - How Does Product Recovery Affect Quality Choice?
Gilvan Souza, Associate Professor, Indiana University, Kelley School
of Business, 1309 E 10th St, Bloomington, IN, 47401,
United States of America, gsouza@indiana.edu, Atalay Atasu
4 - CUT: A New Multi-criteria Approach for Non-additive
Concavifiable Preferences
Nikolaos Argyris, London School of Economics and Political Science,
Houghton Street, London, N1 0HP, United Kingdom,
n.argyris@lse.ac.uk, Jose Figueira, Alec Morton
We study the impact of product recovery (remanufacturing or recycling) on product
quality, where quality increases market valuation for the product. We find that the
recovery cost structure and the presence of take-back legislation significantly impact
quality. Product recovery can be welfare improving, underscoring benefits of
environmental legislation.
We propose a new multi-criteria approach for concavifiable preferences: Concave
UTility (CUT). CUT defines a space of value functions consistent with a DM’s
expressed preferences. CUT has analogies with existing aggregation-dissagregation
approaches, e.g. the UTA procedure, however CUT is more general as it does not
require that preferences are additive. We describe how CUT can be used in an
interactive setting: pre-ordering a finite set of discrete alternatives and multi-criteria
optimization.
3 - The Effect of Remanufacturing on New Products
Vishal Agrawal, Georgia Institute of Technology, 800 W Peachtree St
NW, Atlanta, GA, United States of America,
Vishal.Agrawal@mgt.gatech.edu, Atalay Atasu, Koert Van Ittersum
5 - Studying the Effect of Improved Individual Skills in Negotiation and
Collective Decision Making
Rebeca Díaz, Full Time Teacher, Technological Institute of Superior
Studies of Coacalco, Av. 16 de septiempre No. 54, Cabecera,
Municipal, Coacalco, Edo, de México, México D.F., 55700, Mexico,
rbkdiazt@hotmail.com, Leopoldo Viveros, Mario Chew
In this paper, we experimentally investigate the effect of remanufactured products
on the perceived value of new products. We incorporate this effect to analytically
investigate an OEM’s strategy in the presence of competition from third-party
remanufacturers. Our research shows that an OEM may not always benefit from
preempting third-party remanufacturers. Instead, an OEM may find it more
profitable to allow third-party competitors to remanufacture its products.
Some questions about group decision making relate to the skills of the members, for
instance: Does the group make better decisions than those of its most skilled
member? If the members do not share objectives, how the skills at decision making
and negotiation influence the decision? To study these issues we developed an
environment in which the skills of each member can be controlled, using a
simulated job-sequencing problem as a benchmark and final year engineering
students as subjects.
4 - Complying with Take-Back Legislation: A Cost Comparison and
Benefit Analysis of Compliance Schemes
Gokce Esenduran, The Ohio State University, 2100 Neil Avenue,
Columbus, OH, United States of America,
esenduran_1@fisher.osu.edu, Eda Kemahlioglu-Ziya
We compare three compliance schemes (i.e. individual, collective and collective with
individual financial responsibility) that firms follow to comply with take-back
legislations. We model each scheme as a two-stage Nash game and find the key
market/operating conditions that make one preferable to the others. As the most
cost effective scheme may fall short on environmental benefits, i.e. collection
rate\treatability level, we identify how environmental benefits compare between the
three schemes.
■ WB05
Stochastic Optimization
Contributed Session
■ WB04
Chair: Asad Ata, Southern Methodist University, P.O. Box: 750123,
Dallas, TX, 75275-0122, United States of America, ata.asad@gmail.com
1 - Equity Valuation and Debt Selection via Stochastic Programming
Davi Valladao, PhD Student, Pontifical Catholic University of Rio de
Janeiro, Rua Marqu’s de São Vicente, 225, Rio de Janeiro, RJ,
22451-041, Brazil, davimichel@gmail.com, Geraldo Veiga,
Alvaro Veiga
Decision Analysis III
Contributed Session
Chair: Rebeca Díaz, Full Time Teacher, Technological Institute of Superior
Studies of Coacalco, Av. 16 de septiempre No. 54, Cabecera, Municipal,
Coacalco, Edo, de México, México D.F., 55700, Mexico,
rbkdiazt@hotmail.com
1 - Integrated Multi-Time-Scale and Multi-Organizational-Scale
Decision Making Model
Christian Wernz, Assistant Professor, Virginia Tech, Industrial and
Systems Engineering, 250 Durham Hall (0118), Blacksburg, VA,
24061, United States of America, cwernz@vt.edu, Abhijit Deshmukh
We develop a multistage stochastic programming model for equity valuation and
debt selection for a firm with a predetermined project portfolio. We consider fixed
and floating interest rate debt with different maturities. Moreover, the price of each
corporate bond is given by a risk free valuation multiplied by a discount factor. We
assume this factor to be a concave piecewise linear function of the new debt issued,
with each segment based on different leverage rate levels.
2 - On a Class of Stochastic Programs with Endogenous Uncertainty:
Algorithm and Applications
Bruno Flach, PSR, Praia de Botafogo 228/1701, Rio de Janeiro,
22260020, Brazil, bruno@psr-inc.com
In organizations, hierarchically interacting agents make decisions at different time
scales. Typically, higher level agents make decisions about strategic variables with
lower frequency compared to lower level agents, which make decisions about
operational variables more often. We develop a multiscale decision model for
hierarchical agents, and present an analysis of three-level agent interactions.
We study a class of stochastic programming problems in which the probability
distribution of the random parameters is decision-dependent. We propose a
convexification technique coupled with a cut-generation algorithm for the MINLP
formulation and the incorporation of importance sampling concepts into the
stochastic programming framework so as to allow the solution of large instances.
The applicability of our methodology is illustrated by an example in the area of
power systems’ reliability.
386
3 - A Stochastic Programming Model for Seasonal View Selection
Problem in Database Management Systems
Rong Huang, Research Assistant, North Carolina State University,
484 Daniels Hall, Campus Box 7913, Raleigh, NC, 27695-7913,
United States of America, rhuang@ncsu.edu, Rada Chirkova,
Yahya Fathi
WB08
Bullwhip Effect (BWE) under moving average (MA) and exponential smoothing
(ES) forecasting methods. Results show that: first, demand forecast can reduce BWE
under price-sensitive demand function; second, price forecast can reduce BWE
under certain conditions when customers consider price fluctuation; besides, BWE
under ES is not always significant compared to that under MA.
2 - Product Recoveries in China: Remanufacturing vs. Refurbishing
Yao Chen, Shanghai Jiaotong University, No.535 Fahua Road,
Shanghai, Shanghai, China, yaochen514@msn.com, Fangruo Chen
We introduce the stochastic seasonal view selection problem with random query
sets, and model it as a two-stage stochastic integer programming problem. We
propose exact and inexact methods for solving the problem and present the results
of a computational experiment.
The markets for recovered products in China consist of both remanufactured and
refurbished products, where the former must match the quality limit. Relative to
new products, the two type of recovered products enjoy a cost advantage, but suffer
from a lower willingness-to-pay by the consumers. We characterize the equilibrium
market structure when all the three products compete with each other with a
emphasis on the conditions under which the remanufacturing products can survive
the competition.
4 - A New Hybrid Method for Solving Multistage Stochastic
Programming Problems
Nezir Aydin, Research Assistant, Wayne State University, 4815
Fourth Street, Room: 1067, Detroit, MI, 48202, United States of
America, aydin@wayne.edu, Alper Murat, Leslie Monplaisir
3 - Variable-level Disassembly Planning for Facilitating
Remanufacturing Between Different Products
Yoo S. Hong, Associate Professor, Seoul National University, 599
Kwanakro, Kwanakgu, Seoul, Korea, Republic of, yhong@snu.ac.kr,
Changmuk Kang
In this study, we propose a creative way of combining the Progressive Hedging
Algorithm (PHA) and Sampling Average Approximation (SAA) methods for solving
multi-stage Stochastic Programming (SP) problems such that the exactness and
speed of attaining a solution can be traded-off. Through extensive experimental
results, we demonstrate the effectiveness of this hybrid approach over the pure
strategies (SAA or PHA only) under specific circumstances using multi-product lotsizing problem.
In order to resolve the mismatch between return supply of end-of-life (EOL)
products and demand of a new product, an EOL product has to be disassembled and
remanufactured at a part level, and used for producing a different product. This
study solves a problem of planning disassembly of different kinds of products of
which return and demand change over time. Each product is disassembled into
variable levels according to its return and demand of serviceable parts.
5 - An LP Based State Space Approach to Stochastic Dynamic
Programming Problem
Asad Ata, Southern Methodist University, P.O. Box: 750123, Dallas,
TX, 75275-0122, United States of America, ata.asad@gmail.com,
Eli Olinick, Chester Chambers, Eli Snir
4 - Closed Loop Supply Chains for U.S., Japan and EU Auto Industries
- A System Dynamics Study
Sameer Kumar, Professor of Operations and Supply Chain
Management, Opus College of Business, University of St. Thomas,
Mail # TMH 343, 1000 LaSalle Avenue, Minneapolis, MN, 554032005, United States of America, skumar@stthomas.edu
A linear programming (LP) approach is discussed to solve a stochastic dynamic
programming (SDP) problem. An attempt is made to alleviate the curse of
dimensionality by formulating the problem as a discrete time, infinite horizon,
stochastic dynamic programming model with a finite state space. The model results
as an instance of Unichain Markov Decision Process. The LP produces a profit
maximizing policy and states the likelihood the resulting markov system is in any
particular state.
System Dynamics analysis of the U.S., Japan and EU auto industries’ reverse value
chains was conducted to explore the impact of government regulations, financial
incentives and market pricing for remanufactured and recycle materials on cash
flows and use of such raw materials for car manufacturers in these three market
segments.
■ WB06
Tutorial: Robust Vehicle Routing
■ WB08
Cluster: Tutorials
Invited Session
Location Modeling Applications
Chair: Fernando Ordonez, Associate Professor, University of Southern
California, Department of Industrial and Systems Eng, 3715 McClintock
Ave, Los Angeles, CA, 90007, United States of America, fordon@usc.edu
1 - Robust Vehicle Routing
Fernando Ordonez, Associate Professor, University of Southern
California, Department of Industrial and Systems Eng, 3715
McClintock Ave, Los Angeles, CA, 90007, United States of America,
fordon@usc.edu
Sponsor: Location Analysis
Sponsored Session
Chair: Rajan Batta, Professor and Associate Dean, University at Buffalo
(SUNY), Department of Industrial & Systems Engg, 438 Bell Hall, Buffalo,
NY, 14260, United States of America, batta@buffalo.edu
1 - Ambulance Location, Relocation and Relocation with
Uncertainty Models
Bo Zeng, Assistant Professor, University of South Florida,
Department of IMSE, Tampa, FL, 33620, United States of America,
bzeng@usf.edu, Shengyong Wang
Vehicle routing problems in many industrial applications must take into account
uncertain demand, traffic conditions and/or service times. In this tutorial we present
recent work on the use of robust optimization for vehicle routing problems (VRP)
under uncertainty. We outline different robust VRP models, depending on the
formulation, source of the uncertainty, and correlation in the uncertainty.
Furthermore, we discuss previous computational results that illustrate when such a
robust model is convenient and when it is not. We show with results in two
different applications that robust optimization is useful to find a routing plan when
routes will be adapted to the outcome of the uncertainty.
Various location models for ambulances have been extensively studied. In this talk,
we first present a dynamic relocation model that could be combined with any
existing location models. Then, a stochastic relocation model that includes request
uncertainties will be presented. Finally, numerical study will be given to show the
effectiveness of those models on response times in difference situations.
2 - Centralized Dispatch Approximation for the Transshipment Problem
Dmitry Krass, Professor, University of Toronto, Rotman School of
Management, 105 St. George Street, Toronto, ON, M5S 3E6, Canada,
Krass@Rotman.Utoronto.Ca, Alex Shlakhter
■ WB07
In the transshipment problem a number of retailers facing stochastic demand must
place orders before the demand is known, but can transship inventory once the
demand is realized. We show that by assuming a central depot through which all
transshipments must flow, the computations of the (approximately) optimal
ordering policy are greatly simplified. Moreover, the performance of the
approximate policy is excellent. We also analyze and obtain analytical results for the
monotone policy case.
Supply Chain, Closed-loop I
Contributed Session
Chair: Sameer Kumar, Professor of Operations and Supply Chain
Management, Opus College of Business, University of St. Thomas,
Mail # TMH 343, 1000 LaSalle Avenue, Minneapolis, MN, 55403-2005,
United States of America, skumar@stthomas.edu
1 - Analysis of Bullwhip Effect Under Retailer and Customer
Forecasting with Price-sensitive Demand Function
Yungao Ma, School of Management, Xi’an Jiaotong University,
Shaanxi, China, 710049, Xi’an, 710049, China,
ma.gao@stu.xjtu.edu.cn, Zhiping Yuan, Yufei Huang
In a single two-stage supply chain with one supplier and one retailer, we analyze
the impact of demand forecast by retailer and price forecast by customers on
387
WB09
■ WB10
3 - Facility Location Problem with Network Oligopoly
Paul Berglund, University at Buffalo, 786 West Ferry Street, Buffalo,
NY, 14222, United States of America, berglund@buffalo.edu,
Changhyun Kwon
Managing the Distribution Channel with Competing
Products and Supply Risk
We formulate an equilibrium facility location problem on a discrete network, where
the locating firm acts as the leader in a Stackelberg-Nash-Cournot competitive
equilibrium problem. To maximize expected profits the locating firm must solve a
problem with equilibrium constraints. Finding an optimal solution is hard for large
problems. Therefore a heuristic solution procedure based on simulated annealing is
presented.
Sponsored Session
Chair: Yunzeng Wang, University of California-Riverside, A. Gary
Anderson Graduate School of Mgmt, Riverside, United States of America
1 - Split Award Auctions for Supplier Retention
Aadhaar Chaturvedi, IESE Business School, Av. Pearson 21,
Barcelona, Spain, achaturvedi@iese.edu, Damian Beil,
Victor Martinez de Albeniz
4 - Locating Temporary Depots to Facilitate a Post-Disaster Relief
Operation: A Case Study
Yen-Hung Lin, PhD Candidate, University at Buffalo (SUNY), 438
Bell Hall, Buffalo, NY, 14260, United States of America,
yl48@buffalo.edu, Peter Rogerson, Alan Blatt, Marie Flanigan, Rajan
Batta
Traditionally, buyers use auctions select the lowest-cost supplier. By doing so, they
might alienate the losing suppliers. This involves a future cost of supplier
qualification if they defect from the supply base. This paper considers the trade-off
between the purchasing cost and the qualifying cost paid to maintain the supply
base. We find the optimal split award that minimizes long-run costs and the optimal
supply base size that the buyer should maintain.
A case study through HAZUS simulation software of a historical earthquake scenario
is used to evaluate the performance of a disaster relief operation with a distributed
supply strategy. The distributed supply strategy locates several temporary depots in
the area impacted by a recent earthquake event so that demand can be fulfilled by
either temporary depots or the central depot. The items being supplied are of three
categories (water, food and medicine) and have different priorities.
2 - Nature of Coordination Contracts for Supply Chain Management:
Classifications and Structural Results
Meng Lu, The Chinese University of HK, Shatin, N.T., Hong Kong,
China, mlu@se.cuhk.edu.hk, Houmin Yan, Suresh Sethi
■ WB09
In this paper, based on the group decision-making and game theory, we define a
framework for supply chain contracts and classify into groups. With precise
mathematical definitions, and subsequently developed structural properties and
sufficient conditions, we are not only able to measure the goodness of supply
contracts but also to reveal the nature of the supply coordination. We develop
indexes to measure coordination contracts in terms of coordination strength and
decision sequence dependency.
Behavioral Issues
Sponsored Session
Chair: Mirko Kremer, Pennsylvania State University, 460 Business
Building, State College, PA, 16802, United States of America,
Mirko.Kremer@psu.edu
1 - Explanations of Newsvendor Biases Do Not Square
Neil Bearden, Assistant Professor, INSEAD, 1 Ayer Rajah Ave,
Singapore, 138636, Singapore, Neil.BEARDEN@insead.edu,
Sameer Hasija
3 - Heterogeneous and Nonlinear Frontier Analysis: Supply-Chain
Transaction Cost Perspective
John Liu, Chair Professor, Hong Kong PolyU, CD 401b, Kowloon,
Hong Kong - PRC, lgtjliu@polyu.edu.hk, Jason Jianfeng Mao
Inspired by the works of Williamson (2008), transaction cost economics of supply
chain management is emerging as a challenging research area, due to heterogeneity
and non-linearity of transaction costs as incurred in outsourcing operations of SCM.
We herein develop a degenerative frontier model which incorporates both
heterogeneity and nonlinearity. We obtain convexity properties, and develop a
solution method which converts a DF problem into a sequence of convex problems.
We show that now-conventional explanations of biases in newsvendor experiments
do not hold up to close scrutiny. The accounts implicitly assume that decision
behaviour is invariant with respect to problem framing, but we show that order
quantities are strongly contingent on the way the problem is presented. Finally, we
argue for an eliminitavist stance on explanation in behavioural operations: the
attempt to give simple accounts of decision behaviour in complex problems should
be abandoned.
■ WB11
2 - On the Ability to Identify Pareto-improving Supply Contracts
Mirko Kremer, Pennsylvania State University, 460 Business Building,
State College, PA, 16802, United States of America,
Mirko.Kremer@psu.edu, Tony Haitao Cui
Empirical Research in Operations Management
Sponsored Session
Formal analyses of risk-sharing supply contracts typically focus on identifying
contracts that induce maximal channel efficiency, while allowing for a flexible
allocation of channel profits. As a first step toward a better understanding of the
bargaining process toward such Pareto contracts, we investigate empirically how
sellers and buyers choose from sets of contracts. We further explore how the ability
to identify Pareto-improvements is sensitive to the framing of the contract.
Chair: Vishal Gaur, Associate Professor, Johnson School, Cornell
University, 321 Sage Hall, Ithaca, NY, 14850, United States of America,
vg77@cornell.edu
1 - The impact of New Product Introduction on Plant Productivity in the
NA Automotive Industry
Serguei Netessine, Professor, INSEAD, Boulevard de Constance,
Fontainebleau, 77305, France, serguei.netessine@insead.edu, Manu
Goyal, Anand Gopal, Matthew Reindorp
3 - Revenue Sharing versus Buyback Contracts: Influence of
Supplier Preferences
Karen Donohue, Associate Professor, University of Minnesota,
Carlson School of Management, Minneapolis, MN, United States of
America, donoh008@umn.edu, Yinghao Zhang, Tony Haitao Cui
We empirically estimate productivity losses during new product introductions in the
automotive industry. We show that productivity losses can be mitigated through
manufacturing flexibility and different forms of organizational learning.
Prior analytical research shows that buyback and revenue sharing contracts achieve
equivalent channel-coordinating solutions when applied in a single supplier-buyer
setting. More recently, behavioral research suggests that the two contracts do not
always perform equivalently. We examine how supplier preferences, such as loss
aversion and time discounting, can lead suppliers to prefer one contract type over
the other depending on the ratio of overage and underage costs.
2 - An Empirical Study of Pricing in the U.S. Automobile Industry
Antonio Moreno, The Wharton School, 3730 Walnut St,
Philadelphia, United States of America, amore@wharton.upenn.edu,
Gerard Cachon, Christian Terwiesch
Despite the abundant theoretical literature on dynamic pricing, price postponement
and operational flexibility, there is limited empirical evidence on how firms actually
adjust their prices, and how operational practices play a role in their pricing
decisions. Using a detailed transactional dataset of the US auto industry, we study
the impact of operational strategic decisions on pricing.
4 - Product Quality Choice and Inventory Risk Under Strategic
Consumer Behavior
Robert Swinney, Assistant Professor, Stanford University, 518
Memorial Way, Stanford, CA, 94305-5015, United States of America,
Swinney_Robert@GSB.Stanford.Edu, Sang-Hyun Kim
We analyze a model in which a firm selling a single, seasonal product sets both
product quality and quantity before selling to a population of forward-looking
customers. The size of the market is uncertain to the firm, and customers anticipate
the price path of the product and may strategically delay a purchase to pay a lower
price. We consider the impact of both demand uncertainty and customer behavior
on the optimal quality and quantity of the product.
388
WB14
■ WB13
3 - Improving Retail Store Performance by Incorporating Traffic
Characteristics in Labor Planning
Vidya Mani, The University of North Carolina at Chapel Hill,
The Kenan-Flagler Business School, Chapel Hill, NC, 27599,
United States of America, vidya_mani@unc.edu, Saravanan Kesavan,
Jayashankar Swaminathan
Dynamically Managing Customer Loyalty and Learning
Sponsored Session
Managing store labor is critical to improving customer service as well as controlling
costs for retailers. Using data from a large retailer, we show how labor planning can
be improved by incorporating store traffic characteristics in managerial staffing
decisions.
Chair: Dan Adelman, Professor, University of Chicago, 5807 South
Woodlawn Ave., Chicago, IL, 60637, United States of America,
dan.adelman@chicagobooth.edu
1 - Dynamic Capacity Allocation to Customers Who Remember
Past Service
Adam Mersereau, University of North Carolina, Kenan-Flagler
Business School, Chapel Hill, NC, United States of America,
ajm@unc.edu, Dan Adelman
4 - An Empirical Estimation of the Impact of Airline Flight Schedules on
Flight Delays
Vinayak Deshpande, Purdue University, 100 S. Grant St,
vinayak@purdue.edu, Mazhar Arikan
Airline flight delays have come under increased scrutiny lately, with FAA data
revealing that airline on-time performance was at its worst level in 13 years in
2007. Our goal is to examine the impact of the scheduled time block allocated for a
flight on on-time arrival performance. We combine empirical flight data published
by BTS, with the Newsvendor framework from the Operations literature to conduct
this analysis. Our results show that airlines systematically under-schedule flights.
We study the problem of a supplier dynamically allocating limited capacity among a
portfolio of customers, where each customer’s orders depend positively on the fill
rates provided to her in the past. Customers differ from one another in their
contribution margins, their demand volatilities, and the length of their memories.
We develop an approximate dynamic programming algorithm that rationalizes the
fill rates the supplier should target for each customer.
2 - Optimal Hiring and Retention Policies for Heterogeneous Workers
with Learning
Alessandro Arlotto, University of Pennsylvania, 3730 Walnut Street,
500 Jon M. Hunstman Hall, Philadelphia, PA, 19104, United States
of America, alear@wharton.upenn.edu, Stephen E. Chick,
Noah Gans
■ WB12
Emerging Topics in Supply Chain Management
Supply Chain
Sponsored Session
We study the hiring and retention of heterogeneous workers that learn over time.
We formulate the problem as an infinite-armed bandit and characterize the optimal
hiring and retention policy in detail. We develop approximations that allow the
efficient implementation of the optimal policy and the evaluation of its
performance. We present numerical examples that show, among other things, that
the active screening and monitoring of employees leads to substantial gains.
Chair: Tingting Cui, University of California-Berkeley, Berkeley, CA,
United States of America, tingting@ieor.berkeley.edu
1 - Modeling and Mitigating the Effects of Supply Chain Disruption
on Wargames
Shilan Jin, SUNY at Buffalo, 435 Bell, SUNY at Buffalo,
North Campus, Amherst, NY, 14260, United States of America,
sjin6@buffalo.edu, Zigeng Liu, Jun Zhuang
3 - Signaling Service Quality in Queues
Senthil Veeraraghavan, Assistant Professor, Wharton School of
Business, University of Pennsylvania, 3730 Walnut Street, Jon M.
Huntsman Hall, Suite 500, Philadelphia, PA, 19104,
United States of America, Senthilv@wharton.upenn.edu
We integrate supply chain risk management with a government-terrorist game in
war zones. The equilibrium outcomes of wargames depend on the government’s
resources delivered through military supply chains, which are subject to disruptions.
We study the government’s optimal pre-disruption strategies, including inventory
protection, capacity backup protection and the combination.
We study how a high quality service firm signals quality to differentiate from a low
quality firm through expensive signaling efforts. Rational consumers try to learn
quality through these imperfectly advertised signals. Their decisions are based on
signaling efforts of the firms, congestion in the market, and the service value. We
show that it is likely that a high quality firms may incur lower revenues due to
signaling efforts.
2 - Asymmetries of the Pull-to-Center Effect in the
Newsvendor Experiments
Tianhu Deng, PH. D student, UC, Berkeley, IEOR Department, 4141
Etcheverry Hall, Mail Code 1777, Berkeley, United States of America,
tianhu_deng@berkeley.edu
■ WB14
It has been frequently observed in newsvendor games, the subjects’ average order
quantity lies in between the optimal order quantity and the mid-point of the
demand, in both high profit and low profit settings. This phenomenon is called pullto-center effect. Some researchers found that the pull-to-center effect is stronger in
the high-profit setting than the low profit setting while others found the opposite
result. We present explanations for this discrepancy.
Supply Chain Management IX
Contributed Session
Chair: Nomesh Bolia, Dr, IIT Delhi, #276 Block III, IIT Delhi, New Delhi,
DL, 110016, India, nomesh@mech.iitd.ac.in
1 - Measurement and Optimization of Supply Chain Responsiveness
Sin-Hoon Hum, National University of Singapore, NUS Business
School, 15 Kent Ridge Drive, Singapore, 119245, Singapore,
bizhumsh@nus.edu.sg, Mahmut Parlar
3 - Impact of Social Contagion in Make-to-Stock and Make-to-Order
Supply Chains
Shan Li, Operations Research Scientist, Amazon.com, 605 5th
Avenue South, Seattle, WA, 98104, United States of America,
lisapine@berkeley.edu, Teck Ho, Z. Max Shen
We consider make-to-order supply chains with multiple stages where each stage is
completed in a random length of time. We define the responsiveness of such a
supply chain as the probability that an order placed now will be fulfilled within t
time units. We optimize the responsiveness of the supply chain by maximizing the
probability that the order will be fulfilled within some promised time interval
subject to a budget constraint.
We first analyze the impact of social contagion in a make-to-stock supply chain. We
show that an out-of-stock phenomenon that occurs earlier in a product’s life cycle
always leads to a greater loss in a firm’s customer assets. We then analyze the
impact of social contagion in a make-to-order spply chain. We demonstrate that a
lengthy lead time can slow down social contagion, decelerate customer purchases,
and thus significantly decrease a firm’s total customer assets.
2 - Behavior of a Remanufacturing System in Presence of Varying
Suppliers Reliability for New Product
Suman Niranjan, Assistant Professor, Savannah State University,
College of Business Administration, 3219 College Street, Savannah,
GA, 31404, United States of America, suman1130@gmail.com
4 - Flexible Nonhomogeneous Supply Chain Design Under Supply
Chain Disruptions
Ye Xu, University of California-Berkeley, Berkeley, CA,
United States of America, yex207@berkeley.edu, Z. Max Shen
We look at the flexibility design problem of a general supply chain with unbalanced
structure, and nonhomogeneous demands and suppliers. Besides demand
uncertainty, supply disruption is also considered in our model. We discuss solution
algorithms for a series of models, and show that the marginal value of flexibility
does not diminish as capacity increases. Rather, more flexibility is encouraged when
more capacity is available.
In this paper we study a two-echelon remanufacturing system, which focuses on
what should be the right mix of new and remanufactured components used in the
manufacturing of a new product, and why should we care about the mix?.
Moreover we study this problem in the presence of unreliable suppliers for new
component. We analyze the performance of the system initially by developing a set
of dynamic equations used in simulation based optimization framework.
389
WB15
3 - The Analysis of Performance in One Single and Dual Channels
Zhaoqiong Qin, Associate Professor, North Carolina A&T State
University, 1601 E. Market Street, Greensboro, NC, 27411,
United States of America, zqin@ncat.edu
5 - Generalized Sum-of-squares Cones and Their Applications
David Papp, Rutgers Center for Operations Research, 640
Bartholomew Rd, Piscataway, NJ, 08854, United States of America,
dpapp@rutcor.rutgers.edu, Farid Alizadeh, Ricardo Collado
Suppliers routinely decide whether to distribute their products through one single
channel or dual channels. Conventional wisdom says that dual distribution channels
outperform one single channel based on the whole supply chain’s performance in
the capacity and the supplier’s profit. However, this paper finds that the channel
structure including centralized and/or decentralized in the distribution plays an
important role in these performances.
We consider the cone of sum-of-squares vectors with respect to an arbitrary bilinear
multiplication in a finite dimensional space. We show that these cones are feasible
sets of semidefinite optimization problems, extending Nesterov’s results on real
valued sum-of-squares functions. Different choices of spaces and multiplications
give rise to a diverse set of applications; we show a few in combinatorial
optimization, geometric optimization, and shape-constrained statistical estimation.
4 - Fuzzy Logic Based Methods to Quantify Supply Chain Performance
Nomesh Bolia, Dr, IIT Delhi, #276 Block III, IIT Delhi, New Delhi,
DL, 110016, India, nomesh@mech.iitd.ac.in, Pranav Saxena,
Jalaj Bhandari
■ WB16
Globalization and dynamic market conditions have forced companies to focus on
methods to evaluate the performance of their supply chains and improvise where
needed. Hence there is an increasing interest in quantifying performance. However
there are a lot of uncertainties in supply chain parameters (hence performance
measures), and relative importance of these performance measures. We apply fuzzy
logic to address these issues and develop an appropriate performance index for
supply chains.
Remanufacturing
Contributed Session
Chair: Pei-Fang Tsai, Assistant Professor, National Taipei University of
Technology, 1, Sec. 3, Chung-hsiao E. Rd., Taipei, 10608, Taiwan - ROC,
ptsai@ntut.edu.tw
1 - Inventory Management in Closed-loop Supply Chains Under
Non-stationary Demand
Ibrahim Dogan, Wayne State University, Industrial & Manufacturing
Engineering, 4815 Third Street, Detroit, MI, 48202, United States of
America, aq9742@wayne.edu, Ratna Babu Chinnam
■ WB15
Convex Optimization
This study aims to analyze remanufacturer’s inventory control policy under nonstationary demand. The objective is to decide on virgin product replenishment
quantities under used product returns. The exact solution to this inventory control
problem in our setting is complex and time demanding. We offer and analyze a
number of different sub-optimal policies.
Contributed Session
Chair: David Papp, Rutgers Center for Operations Research, 640
Bartholomew Rd, Piscataway, NJ, 08854, United States of America,
dpapp@rutcor.rutgers.edu
1 - Convex Relaxation for the Planted k-disjoint-clique Problem
Brendan Ames, PhD Candidate, University of Waterloo, 200
University Avenue West, Waterloo, ON, N2L3G1, Canada,
bpames@math.uwaterloo.ca, Stephen Vavasis
2 - Used Product Returns Policy Under Demand and
Return Uncertainty
Samar Mukhopadhyay, Professor, SungKyunKwan University-GSB,
53 Myungryun dong 3-ga, Jongno gu, Seoul, 110745, Korea,
Republic of, samar@skku.edu, Robert Setaputra
We consider the k-disjoint-clique problem. For a given graph G, the problem is to
find within the graph k disjoint cliques that cover the maximum number of nodes
of G. The k-disjoint-clique problem is NP-hard, but we show that a convex
relaxation can solve it in polynomial time for certain input instances. The input
instances for which our algorithm finds the optimal solution consist of k disjoint
large cliques that are then obscured by noise edges and noise nodes.
Reusing still usable components from a used up product makes sound
environmental and economic sense. Uncertainty in the quantity of returns and
demand complicates the operation. Our decision variable is the return policy,
characterized by the amount refunded to the consumer. The trade-off is between
increased revenue due to reduced input cost and increased cost due to higher return
amount. Optimal return policy and managerial insights on sensitivity analyses will
be presented.
2 - A Convexity Result for an (S-1,S) Inventory Model Under
Time Limits on Backorders
Emre Tokgoz, Emre.Tokgoz-1@ou.edu, Hillel Kumin
3 - Remanufacturing Planning with Variable Quality Returns
Xiaoning Jin, PhD Student, University of Michigan, 2300 Hayward
Street, Ann Arbor, MI, 48109, United States of America,
xnjin@umich.edu, S. Jack Hu, Jun Ni
The (S-1,S) inventory model with time limits on backorders has previously been
solved by minimizing a function of two variables, one of which is integer. We
investigate the convexity of the objective function and develop new convexity
results for functions with m integer and n continuous variables.
There is a need for remanufacturers to grade quality of the returns prior to recovery
processes because of the quality uncertainty of returns.Since some returns require
more capacity and cost to bring the unit up to a required quality standard than
others,quality variability information will have great impacts on remanufacturing
decisions.We’ll develop a quality-dependent remanufacturing model to obtain the
optimal control of the remanufacturing quantity that minimize the expected total
cost.
3 - A Holloway-Inspired Enhancement for the Frank-Wolfe Approach to
the Convex Hull Problem
Xinyu Wang, PhD Student, Southern Methodist University,
P.O. Box 750123, Dallas, TX, 75275-0122, United States of America,
xwang@smu.edu, Richard Helgason
The extreme points of a convex hull can be found by using the Frank-Wolfe
quadratic programming method. We investigate a novel Holloway-Inspired
enhancement to the Frank-Wolfe method. The enhancement tries to avoid zigzag in
the later stage of the projection point computation and gives us faster convergence.
Experimental results indicate the enhancement leads to a significant speedup.
4 - Best Partial Disassembly Strategy for Retrievable
End-of-Life Products
Pei-Fang Tsai, Assistant Professor, National Taipei University of
Technology, 1, Sec. 3, Chung-hsiao E. Rd., Taipei, 10608, Taiwan ROC, ptsai@ntut.edu.tw
4 - A Polyhedral Projection Method for Solving Variational Inequalities
Sudhanshu Singh, PhD Student, UNC Chapel hill, UNC Department
of STOR, B 44, hanes hall, CB# 3260, UNC Chapel Hill, Chapel hill,
NC, 27599-3260, United States of America, sssingh@email.unc.edu,
Shu Lu
A product reaches its end of life when it is malfunctioned or undesirable to the
users. This research focuses on returned products in two categories: those are
qualified to be repaired or remanufactured, and those can be retrieved for useable
parts. The best partial disassembly strategy is proposed and formulated as a
multicommodity flow problem with applicability established. The objective is to
obtain maximum potential benefits inherent in the end-of-life production planning.
Most projection based methods for solving variational inequalities suffer from the
drawback that the projection on a general convex set is not easy to find. This talk
presents a projection method which replaces the feasible set by a polyhedral convex
set in each iteration. The proposed algorithm uses (sub)gradient information to
generate the polyhedron. It is easy to implement and its convergence is analyzed
under some mild assumptions.
390
■ WB17
■ WB18
Decision Making in Interdependent Systems
OR in Practice II
Contributed Session
Sponsor: CPMS, The Practice Section
Sponsored Session
Chair: Kash Barker, Lecturer, University of Oklahoma, 202 W. Boyd,
Room 124, Norman, OK, 73019, United States of America,
kashbarker@ou.edu
1 - Decision Analysis Tool for Assessing Hurricane Impact on Regional
Workforce Productivity
Joost Santos, Assistant Professor, Engineering Management and
Systems Engineering, The George Washington University,
1776 G Street NW, Rm 164, Washington, DC, 20052,
United States of America, joost@gwu.edu
WB19
Chair: Brian Lewis, Vice President, Professional Services, Vanguard
Software, 1100 Crescent Green, Cary, NC, 27518, United States of
America, brian.lewis@vanguardsw.com
Co-Chair: Bjarni Kristjansson, President, Maximal Software, Inc., 933 N.
Kenmore St., Suite 218, Arlington, VA, 22201, United States of America,
bjarni@maximalsoftware.com
1 - An Integrated Framework of Service Quality for Global Delivery of
Contact Center Services
Nanda Kambhatla, Senior Manager, Human Language Technologies,
IBM India - Research, ‘D’ Block, Embassy Golf Links, Koramangala
Inner Ring Road, Bangalore, 560071, India, kambhatla@in.ibm.com,
Mayuri Duggirala, Ramana Polavarupu, Dinesh Garg
This research develops a workforce recovery model based on input-output analysis
to estimate sector inoperability and economic losses. Based on our simulated
hurricane scenarios, service sectors in Virginia suffer the largest workforce
productivity impact-accounting for nearly 40% of the total economic losses.
Sensitivity analysis of inoperability and loss reduction objectives can provide insights
on identification and prioritization of critical workforce sectors to expedite disaster
recovery.
We present a framework of provider-perceived service quality for contact center
services, incorporating key dimensions of service quality based on interviews with
service providers in contact center services. Our findings indicate that benchmarking
and error management are significant provider-perceived dimensions of service
quality in contact center services which predict business performance outcomes.
Avenues for further research, as well as insights for research and practice are
suggested.
2 - Resilience Assessment and Improvement of Urban
Infrastructure Systems
Leonardo Dueñas-Osorio, Assistant Professor, Rice University, 6100
Main Street, MS-318, Houston, TX, 77005, United States of America,
leonardo.duenas-osorio@rice.edu, Min Ouyang
2 - Decision Support System for Continuous Production
Krystsina Bakhrankova, Researcher, Institute of Technology and
Society - Applied Economics, S. P. Andersens Veg 5, Box 4760
Sluppen, Trondheim, 7465, Norway,
Krystsina.Bakhrankova@sintef.no
This paper proposes an annual resilience metric, which reflects the capacity of
infrastructure systems to resist, absorb and recover from all possible disruptive
events. Taking the transmission power grid and gas transmission system of in Harris
County, Texas, as an example, the effectiveness of different resilience improvement
measures are analyzed and discussed. This study can provide insight and direction to
design and retrofit resilient interdependent infrastructure systems.
The paper develops a model-based decision support system (DSS) for a European
chemical plant with a multi-stage continuous production process. The system
comprises two modules - energy cost minimization and output maximization, where
a gist of the two underlying formulations is presented. The planning tool is tested on
real data instances - it reflects the essence of the researched production process,
provides substantial energy cost savings and improved production capacity
utilization.
3 - Interdependency Models to Compare Industry Preparedness and
Reactive Strategies to Disruptive Events
Cameron MacKenzie, Graduate Student, Industrial Engineering,
University of Oklahoma, 202 W. Boyd, Room 124, Norman, OK,
73019, United States of America, cmackenzie@ou.edu, Kash Barker
We use a risk-based interdependency model to quantify the effect of preparedness
strategies such as maintaining inventory and the effect of reactive strategies such as
choosing alternate transportation routes or different suppliers if a disruptive event
occurs. We examine the conditions that incentivize industries to prepare for a
disruptive event and how those decisions impact their reactions to a supply chain
disruption. We deploy the model with a case study using actual commodity data.
3 - Optimizing Long-range Plans at Novartis
Brian Lewis, Vice President, Professional Services,
Vanguard Software, 1100 Crescent Green, Cary, NC, 27518,
United States of America, brian.lewis@vanguardsw.com
Long-range strategic planning decisions are not easily modeled with classic
optimization techniques. Using Monte Carlo simulation-based forecasting,
simulation optimization, and grid computing, Vanguard Software built a drug
development pipeline model for Novartis which forecasts long-range R&D
performance and optimizes strategic decisions such as investments in new drugs. In
our presentation, we discuss the underlying model, lessons learned, and other
practical issues.
4 - Dynamic Analysis of Interdependent Inoperability in Multi-modal
Transportation Networks
Raghav Pant, Graduate Student, Industrial Engineering,
73019, United States of America, Raghav.Pant-1@ou.edu,
Kash Barker
We study time-dependent production losses to regions due to disruptions in
important transportation facilities (e.g., ports), by integrating the Dynamic
Inoperability Input-Output Model (DIIM) with a network queuing model. Network
model-driven initial inoperability and recovery time estimates strengthen our ability
to evaluate supply chain risk management options and enhance risk management
decisionmaking. Examples using commodity flow data for inland port disruptions
are illustrated.
■ WB19
Revenue Management of Opaque and
Non-traditional Channels
Sponsored Session
5 - Impact of Disasters on National Freight Flows
Saniye Gizem Aydin, Graduate Student, Industrial Engineering,
73019, United States of America, gizemaydin@ou.edu,
P. Simin Pulat, Guoqiang Shen, Manjunath Kamath, Ricki Ingalls
Chair: Benjamin Marcus, Suffolk University, 8 Ashburton Place, Boston,
MA, United States of America, bmarcus@suffolk.edu
1 - Valuation of Opaque Products
Leo MacDonald, Assistant Professor, Coles College of Business, KSU,
Kennesaw, GA, United States of America, lmacdon4@kennesaw.edu,
Benjamin Marcus
Transportation systems are vulnerable to disasters and absolutely vital for the
economy. There are relatively few studies concerning the regional freight flow
impact of the disaster, even fewer on national impact. Northridge Earthquake,
Hurricane Katrina and I-40 Bridge collapse cases are studied. A spatial input-output
model, distance and traffic volume based changes are used for measuring the
importance, and the influence on decision making within the interdependent freight
flow environment.
Service providers (airlines, hotels, etc) often use opaque sales channels (Hotwire,
Priceline) to increase revenues. A fundamental challenge for these providers is
setting appropriate rates. Set rates too high and no purchase occurs; set rates too
low and forgo the additional revenue. The focus of this research is to determine
customer valuation of opaque versus non-opaque services through a choice
experiment and develop a discrete-choice model to support the decision making
process.
391
WB20
2 - Pricing Opaque and Traditional Channels Jointly
Benjamin Marcus, Suffolk University, 8 Ashburton Place, Boston,
MA, United States of America, bmarcus@suffolk.edu
■ WB21
Despite the benefits to both firms and consumers, there are distinct challenges to
selling products through opaque channels. We develop a model of a service provider
selling inventory across a traditional channel and an opaque channel in order to
identify optimal pricing policies in this setting. In addition, we use this model to
explore the effects that different characterizations of customer behavior and product
commoditization on the opaque channel can have on these policies.
Green Supply Chain Management
Sponsored Session
Chair: Vipul Jain, Assistant Professor, Indian Institute of Technology
Delhi, Department of Mechanical Engineering, Indian Institute of
Technology Delhi, New Delhi, 110016, India, vjain@mech.iitd.ac.in
1 - A Green Approach to Supplier Selection
Amit Kumar, Research Scholar, Indian Institute of Technology,
Department of Mechanical Engineering, Delhi, New Delhi, India,
akumar@icfi.com, Vipul Jain
■ WB20
Pricing and Revenue Management I
As the climate change movement gathers momentum, there’s a pressing need to
assess suppliers based on their environmental performance along with other criteria.
This paper proposes a comprehensive approach based on Data Envelopment
Analysis with Carbon Footprint monitoring. The approach applies to heterogeneous
suppliers and incorporates region specific emission compliance standards as well.
Overall, it encourages suppliers to go green and cut down their emissions to survive
the competition.
Contributed Session
Chair: Craig Sorochuk, Assistant Professor of Decision Science, University
of Wyoming, 1000. East University Avenue, Department of MGMT and
MKT (#3275), Laramie, WY, 82071, United States of America,
csorochu@uwyo.edu
1 - HOT Lane Pricing for Revenue Generation and Congestion
Management: An Analysis of Demand Responses
Lin Qiu, Wilbur Smith Associates, 317 Center St. N, Vienna, 22180,
United States of America, lin.w.qiu@gmail.com, Lei Zhang
2 - Carbon Footprint, Information Disclosure, and Shareholder Pressure
Chien-Ming Chen, UCLA Institute of the Environment, La Kretz
Hall, Suite 300, Box 951496, Los Angeles, CA, 90095, United States
of America, cmchen@ioe.ucla.edu, Charles Corbett, Magali Delmas
High Occupancy Toll Lane has attracted significant interests as a means for
congestion management and revenue generation. Using combined stated-preference
and revealed-preference data for the I-394 corridor, this study develops models to
capture the inter-relationships between pricing schemes, travelers’ mode choices
and dynamic attitudes towards HOT lanes. The estimated attitude and behavior
changes form a reliable basis for projecting revenues and assessing congestion
mitigation effects.
This study examines the causal relationship between corporate carbon efficiency,
voluntary information disclosure, and shareholder’s pressure for greener business
practices. Our analysis draws on the newly compiled direct and supply chain
emission inventories of over 1000 public companies in North America. In the
presentation we will present our preliminary findings.
3 - Evaluation and Management on Logistics Carbon Emission
Xiao Qing Wang, IBM Research, Building 19 Zhongguancun
Software Park, Beijing, China, xqwangxq@cn.ibm.com, Jin Dong,
Hongwei Ding, Minmin Qiu, Wei Wang
2 - Market Share Characterization Through Scenario Analysis
Amit Shinde, Research Associate, Arizona State University,
699 S. Mill Avenue, Tempe, AZ, 85281, United States of America,
amit.shinde@asu.edu, Mani Janakiram, George Runger
Logistics carbon emission management is addressed and carbon emissions from
several key operational stages in logistics industry are studied and evaluated. A
general logistics carbon emission evaluation framework considering different
transportation modes, different warehouses and different carry modes is proposed.
Carbon emission evaluation methods on transportation, storage and carry
operational stages are presented.
The supply chain interactions within the high-technology industry are very
complex. Multiple products with moderate differences in performance and price
compete within the same market segment. We present data mining models for
characterizing elements of such supply chains. These models are capable of
assimilating knowledge from a variety of business scenarios, expert judgment and
historical trends.
4 - Measuring Carbon Emissions From Intermodal Freight Operations
Anthony Craig, PhD Candidate, MIT, 77 Massachusetts Ave,
E40-222, Cambridge, MA, 02139, United States of America,
tcraig@mit.edu, Edgar Blanco, Yossi Sheffi
3 - Designing Public Storage Warehouses with Customer Choice
Yeming Gong, EM Lyon Business School, 23 Avenue Guy de
Collongue, Ecully, France, gong@em-lyon.com
Estimating the carbon emissions from intermodal shipments is difficult for shippers
due to limited information and the complexity of intermodal operations. The
structure of the rail network, terminal locations, and relative efficiency of rail and
drayage operations all impact the actual emissions. Using data from an intermodal
freight operator we compare the calculated carbon emissions for a set of shipments
with the results obtained from popular carbon estimation methods.
Public storage is a booming industry. A major question is how to design public
storage facilities to fit market segments to maximize revenue. This paper propose a
method to design public storage warehouses with considering the choice behavior of
customers. We solve the problem by column generation.
4 - Computing Regulated Bertrand-Nash Equilibrium Prices Under
Mixed Logit Demand
William Morrow, Assistant Professor, Iowa State University, 2014
Black Engineering Building, Ames, 50011, United States of America,
wrmorrow@iastate.edu
■ WB22
Bertrand-Nash equilibrium prices have been used to analyze mergers, new product
introductions, and regulatory policy in large differentiated product markets. We
present a framework with regulatory costs that may not be differentiable, as with
the Corporate Average Fuel Economy Standards. Two nonsmooth fixed-point
formulations of the first-order conditions are shown to provide reliable and efficient
methods for computing equilibrium prices in a large-scale example from the
automotive industry.
Workforce Management
Sponsored Session
5 - The Newsvendor Problem with Pricing and Secondary Revenues
Craig Sorochuk, Assistant Professor of Decision Science, University of
Wyoming, 1000. East University Avenue, Department of MGMT and
MKT (#3275), Laramie, WY, 82071, United States of America,
csorochu@uwyo.edu, John Wilson
Chair: Foaad Iravani, University of California-Los Angeles, Anderson
School of Management, 110 Westwood Plaza, Los Angeles, CA, 90095,
United States of America, firavani@anderson.ucla.edu
1 - Skill Mix and Cross-Training in Professional Service Firms
Vincent Hargaden, PhD Student, Rensselaer Polytechnic Institute,
Industrial & Systems Engineering Dept, 110 8th Street, Troy, NY,
12180, United States of America, hargav@rpi.edu, Jennifer Ryan
We present an expected profit model for a newsvendor who receives revenues from
selling primary items as well as from selling secondary items that are only available
if a primary item has already been purchased. Numerical examples are provided for
a newsvendor whose primary items for sale are tickets to a performance event and
whose secondary items for sale are concessions items, parking, etc.
A comprehensive mixed integer programming model has been developed for the
workforce planning process in professional service firms. We will present results
from the model which show the impact of skill mix, skill capability levels and crosstraining on key performance metrics such as project completion rates, staff
utilization and profit.
392
WB25
■ WB24
2 - A Hiring Plan Model for Call Center Management
Tao Huang, Progressive Insurance, 6300 Wilson Mills Rd,
Mayfield Village, OH, 44143, United States of America,
Tao_Huang@progressive.com, Janet Dolohanty, Steve Callitsis
Joint Session SPPSN/ HAS: Emergency Medical
Services: New Directions
We have developed a hiring plan model for call center management. The model
identifies locations and schedules for the hiring need defined by the capacity
planning and staff-on-hand while taking into account site specific monetary
variables and nonmonetary constraints. The model outputs the optimal combination
of schedules that minimizes hiring cost and specifies the agents required to improve
the peak-hour service level performance.
Sponsor: Public Programs, Service and Needs/ Health Applications
Sponsored Session
Chair: Laura McLay, Assistant Professor, Virginia Commonwealth
University, 1015 Floyd Ave, Box 843083, Richmond, VA, 23284,
United States of America, lamclay@vcu.edu
1 - A Markov Chain Model for an EMS System with Repositioning
Armann Ingolfsson, University of Alberta, Edmonton, AB, Canada,
armann.ingolfsson@ualberta.ca, Ramon Alanis, Bora Kolfal
3 - The Soft Resource Allocation Problem
Foaad Iravani, University of California-Los Angeles, Anderson School
of Management, 110 Westwood Plaza, Los Angeles, CA, 90095,
United States of America, firavani@anderson.ucla.edu, Sriram Dasu,
Reza Ahmadi
We propose and analyze a Markov chain model of an Emergency Medical Services
system that repositions ambulances using a compliance table policy, which is
commonly used in practice. We validate the model against a detailed simulation
model. We demonstrate that the model provides accurate approximations to such
performance measures as the response time distribution and the distribution of the
number of busy ambulances, and that it can be used to identify near-optimal
compliance tables.
We propose optimization models for workforce allocation in a leading software
company that produces tax software. Every year, the firm struggles with a high
workload imposed by changes in tax forms announced by the IRS. In this
competitive market, any delay in the release of the product leads to significant
losses. We develop models for organizing and staffing the development activities to
meet the deadline at the lowest cost.
2 - An Equitable EMS Location Model: Minimizing Envy Toward
Neighbors’ Chance of Access to Service
Sunarin Chanta, PhD Student, Clemson University, 203 Freeman
Hall, Department of Industrial Engineering, Clemson, SC, 29634,
United States of America, schanta@clemson.edu, Maria Mayorga,
Laura McLay
■ WB23
Municipal Waste Management, Analytics and
Optimization
The model is developed for finding optimal locations in order to balance disparity in
service between zones. The objective is to minimize the sum of “envy” among all
zones with respect to an ordered set of p operating EMS stations weighted by the
proportion of demand in each zone. Tabu search is provided to solve the problem.
The performance of the proposed model is tested and compared to other location
models such as the p-center and maximal-covering-location (MCLP) problems.
Sponsored Session
Chair: Heng Cao, CTO for Business Analytics & Optimization, IBM China
Research Center, A2/F, Diamond, Zhong Guang Cun Software,
Haidian District, Beijing, 100193, China, hengcao@us.ibm.com
1 - Decision Support System for Municipal Solid Waste Collection
using Forecasting and Optimization
Tianzhi Zhao, IBM Research - China, Diamond Building A, ZGC
Software Park, 8 Dongbeiwang West Road, Beijing, 100193, China,
zhaotzhi@cn.ibm.com, Jun Zhang, Jin Dong, Heng Cao, Wenjun Yin
3 - Estimating Travel Speeds in Road Networks From GPS Data
Shane Henderson, Professor, Cornell University, School of ORIE,
Rhodes Hall, Cornell University, Ithaca, NY, 14853, United States of
America, sgh9@cornell.edu, Dawn Woodard, Brad Westgate,
David Matteson
We estimate the speeds vehicles travel on road networks from widely spaced GPS
readings as recorded by ambulances. We use a Bayesian formulation and estimate
the posterior distribution of road travel speeds and other quantities using Markov
chain Monte Carlo (MCMC). In this talk I will sketch the problem and data,
describe the MCMC algorithm, and present some sample results.
Municipal solid waste management (MSWM) is becoming a major issue facing cities
around the world due to rapid urbanization and growth of population. In this paper,
an analytics based decision support system is proposed for MSWM. The system
model is composed of two components, one for waste generation prediction,
another one for collection vehicle routing optimization. A GIS application is
integrated into the system to provide route information to as well as map out the
outputs from the model.
4 - Fire Department and Other Emergency Medical Service
John Hall, National Fire Protection Association, Norwood, MA,
United States of America, jhall@NFPA.org
2 - Disturbance Analysis Model for the Maintenance Plan of Power Grid
Feng Jin, Dr., IBM Reaserch - China, Bulding 10, 399 Keyuan Road,
Pudong, Shanghai, 201203, China, jinfsh@cn.ibm.com, Hairong Lv,
Jun Luo, Wenjun Yin, Jin Dong, Qiming Tian
People with emergency medical conditions may call an ambulance, possibly fire
department based, and may seek medical assistance at any of several locations. This
paper will discuss concepts and data sources and uses for a comprehensive system to
track the flow of people in and out of emergency medical service.
To keep the maintenance plan of power gird stable, especially to avoid chainreaction, a probability model is proposed to analyze the effected plans once a plan is
disturbed by various factors. In this model, we consider not only the traditional
variation of start time, but also the variation of process time and workload under
the complex grid topology. A case in a typical Chinese power company is studied to
validate the model. The result shows the plan change rate is greatly reduced.
■ WB25
Transportation, Planning I
3 - An Effort Estimation Model in Project Delivery using Hidden
Setup Cost
Saeed Bagheri, IBM T J Watson Research Center, 1101 Kitchawan
Road, Yorktown Heights, NY, 10598, United States of America,
sbagher@us.ibm.com, Nianjun Zhou, Krishna Ratakonda
Contributed Session
Chair: David Novak, Assistant Professor, University of Vermont,
55 Colchester Ave., Kalkin 310, Burlington, VT, 05405-0157,
United States of America, dnovak@bsad.uvm.edu
1 - Exploring Theoretical Properties of Bounded Rational User
Equilibrium Flow Distributions
Yingyan Lou, Assistant Professor, The University of Alabama, A127K
Bevill Building, Box 870205, Tuscaloosa, AL, 35405,
United States of America, ylou@eng.ua.edu
We discuss the relationship between delivered projects and required effort. In
particular, we analyze the logarithmic model and its shortcomings in required effort
estimation for large projects. We introduce the hidden setup cost and its related
linear model and explain how its existent leads to the above behavior in logarithmic
models. Our proposed model facilitates effort estimation for project delivery in
services and manufacturing. We illustrate this, using projects in software
development.
This paper investigates theoretical properties of the boundedly rational user
equilibrium (BRUE) flow set for transportation networks. Probabilistic methods are
explored to address the uncertainty in link flows characterized by the non-convex
BRUE flow set. Entropy maximization is used to identify the most likely link flow
pattern. Finite sampling approaches are also investigated to derive various measures
from assumptions on the continuous link flow probability space over the BRUE flow
set.
393
WB26
2 - Toolkit for Anticipating and Evaluating Roadway Expansion and
Tolling Impacts
Daniel Fagnant, Graduate Research Assistant, The University of
Texas at Austin, ECJ Suite 6.9, MailCode C1761, Austin, TX, 78712,
United States of America, annette.perrone@engr.utexas.edu,
Kara Kockelman, Chi Xie
3 - Bayesian Analysis of Discrete Time Queueing Networks with a
Gridlock Prediction Application
Toros Caglar, George Washington University, 2201 G St., NW, Funger
Hall, Suite 415, Washington, DC, 20052, United States of America,
toros@gwu.edu, Refik Soyer
Analysis of discrete time queues and their networks have been mostly prevalent in
the context of computer and communication systems. In this study, we aim to
utilize a Bayesian approach for the analysis of these queues with an application in
emergency room (ER) gridlock prediction, which requires transient analysis. We will
also address the challenges presented by the large state space formed by the ERhospital network and the MCMC simulation necessitated by the Bayesian analysis.
We present a new toolkit for forecasting the traffic volumes, travel times, network
reliability, emissions, and safety impacts of roadway expansion and tolling projects.
Trip tables are estimated using constrained maximum entropy methods, based on
link-level traffic counts. Incremental logit models anticipate mode and time of day
splits. All impacts are monetized and compared over project lifetimes, to generate
benefit-cost ratios and other success indicators for Austin case studies.
4 - Bayesian State Space Modeling of Mortgage Default Risk
Tevfik Aktekin, Assistant Professor of Decision Sciences, University of
New Hampshire, 15 Academic Way, Department of Decision
Sciences, Durham, NH, 03824, United States of America,
tevfik.aktekin@unh.edu, Refik Soyer, Feng Xu
3 - Simulation of Vessel Traffic and Dredging Impact Analysis in
Delaware River
Ozhan Alper Almaz, PhD Student, Rutgers University, Industrial &
Systems Engineering Departm, 100 Brett Road, Piscataway, NJ,
08854, United States of America, alperalmaz@gmail.com,
Tayfur Altiok
We consider discrete time Bayesian state space models with Poisson measurements
to model the mortgage default risk at the aggregate level with a stochastic default
rate and macroeconomic covariates. We discuss parameter updating and estimation
using Markov chain Monte Carlo methods where the use of the efficient forward
filtering backward sampling algorithm within a Gibbs sampler is developed. We use
actual U.S. residential mortgage data and discuss insights gained from Bayesian
analysis.
We considered modeling of vessel traffic in the Delaware River Main Channel. A
high fidelity simulation model was developed to investigate effects of deepening and
dredging in the River on the navigational efficiency based on several assumptions.
In this regard, vessel calls to terminals, lightering and barge operations, tidal and
navigational rules in the River, terminal and anchorage properties and vessel
profiles were considered.
4 - Evaluating the Effects of Trip Importance on System-Wide
Performance in Transportation Networks
David Novak, Assistant Professor, University of Vermont,
55 Colchester Ave., Kalkin 310, Burlington, VT, 05405-0157,
United States of America, dnovak@bsad.uvm.edu
■ WB27
We introduce measures for evaluating network robustness and identifying and
ranking the most critical or important links in a transportation network called the
Network Robustness Index, and comparing disparate networks using a scalable,
system-wide performance over all links in the network called the Network Trip
Robustness. We show that the relationships between network robustness, the
capacity-disruption level, and network connectivity are non-linear and are not
necessarily intuitive.
Contributed Session
■ WB26
We analyze a class of problems which determines the relocation and inventory plan
of a single facility over a finite horizon in order to meet dynamic customer
demands. Dynamic programming algorithms are presented to solve the problem
under different objective functions and construct the efficient frontier for biobjective problems, most of which run in polynomial time.
Network Optimization I
Chair: Chase Rainwater, University of Arkansas, INEG Department,
Fayetteville, AR, 72701, United States of America, cer@uark.edu
1 - Integrated Dynamic Single Facility Location and Inventory
Planning Problems
Jiaming Qiu, Student, Rensselaer Polytechnic Institute,
110 8th St., Troy, NY, 12180, United States of America, qiuj@rpi.edu,
Thomas Sharkey
Joint Session DM/ ICS: Bayesian Computational Issues
in Data Mining
2 - Hybrid Wired-cum-wireless Sensor Network Location-allocation
Problem in Industrial Environment
Sima Maleki, Graduate Research Assistant, University of
Tennessee/Industrial and Information Engineering Department,
Knoxville, Knoxville, TN, 37996, United States of America,
smaleki@utk.edu, Mohammad Mehdi Sepehri, Hamid Farvaresh,
Rapinder Sawhney
Sponsor: Data Mining/ Computing Society
Sponsored Session
Chair: Tevfik Aktekin, Assistant Professor of Decision Sciences, University
Of New Hampshire, 15 Academic Way, Department of Decision Sciences,
Durham, NH, 03824, United States of America, tevfik.aktekin@unh.edu
1 - Modeling Brazilian Swap Curve in a Hidden Markov Framework with
Macroeconomic Variables
Richard Munclinger, Economist, IMF, 1301 20th Street, NW, Apt.
107, Washignton, DC, 20036, United States of America,
richardmunch@gmail.com
A hybrid wired-cum-wireless sensor network consists of a wireless network and a
wired backbone. The proposed designs consider limitations of wireless
communication and constraints in industrial applications to minimize the network
cost over a life of a network. The joint problem of configuring the hybrid network,
locating the nodes and sensor clustering is formulated as a Mixed Integer Nonlinear
Programming model. Results illustrate the cost effectiveness and longevity of hybrid
configuration.
We apply a hidden Markov model of the term structure to modeling Brazilian swap
rates. We find that multiple regimes are identified in the data and that
macroeconomic variables improve time series fit without destroying regime
dependency. This work has two main contributions. Firstly, we include
macroeconomic variables in conjunction with a hidden Markov framework.
Secondly, we propose and apply a Bayesian MCMC algorithm to estimate hidden
Markov models of the term structure.
3 - Social Optimality and Pricing in Shared Computing Centers
Ishai Menache, postdoc, MIT, 77 Massachusetts avenue, 32-D632,
Cambridge, MA, 02139, United States of America, ishai@mit.edu,
Nahum Shimkin, Asuman Ozdaglar
Motivated by the recent advent of cloud computing facilities that offer online
computing power on demand, we consider a large service facility that offers
simultaneous service to a large number of heterogeneous users. Our main concern
here is in maximizing the social utility, which comprises of the users’ service utility
minus their delay cost. We show that the social optimum may be achieved by
simple per-unit pricing, which charges a fixed amount per unit time and resource
from all users.
2 - Explaining HIV Mortality, Bayesian Spatial Models Applied with
MCMC Methods
Rasim Muzaffer Musal, Assistant Professor, Texas State University,
404 Rio Grande apt 209, Austin, TX, 78701, United States of
America, rm84@txstate.edu, Tevfik Aktekin
We propose Bayesian Zero Inflated Poisson models to investigate the effects of
poverty and inequality on the number of HIV related deaths in NY counties. In
doing so, we quantify inequality via the Theil Index and Poverty via the ratios of
the two Census 2000 variables. MCMC methods are utilized in eliciting posteriors.
We present the computational complexities that are present in these methods and
emphasize the methods for spatial effects.
4 - Methodologies for Solving Dynamic Fortification Problems
Chase Rainwater, University of Arkansas, INEG Department,
Fayetteville, AR, 72701, United States of America, cer@uark.edu,
Huy-Nhiem Nguyen, Ed Pohl, Scott J. Mason
The fortification of critical infrastructure elements is an issue of notable importance.
However, research in this area has studied the problem of fortification from purely a
static perspective. This work presents a dynamic model that considers the temporal
impacts of resource allocation decisions in a potentially changing infrastructure.
Specifically, we propose decomposition-based solution approaches to solve this
general class of problems.
394
■ WB28
WB30
3 - Detection of Potential Failure Wafers Based on Fail Bit Counts Data
Seung Hoon Tong, Principal Engineer, Samsung Electronics Co., Ltd.,
San#16 Banwol-Dong, Gyeonggi-Do, Hwasung-City, 445-701, Korea,
Republic of, shtong@samsung.com, In Kap Chang, Jeong Hee
Hwang, Kun Han Kim, Seung Sik Jung
Prognostics and Health Management
(PHM / Sensors / RFID)
We present a method for detection of potential failure wafers based on fail bit
counts data from wafer electrical test stage in semiconductor manufacturing. The
number of fail bit each wafer has superior capability for classifying potential failure
wafers than wafer yield itself. We developed two quality measures considering the
magnitude and clustering level of fail bit patterns and showed real applied
examples.
Sponsored Session
Chair: Sagar Kamarthi, Associate Professor, Northeastern University,
360 Huntington Ave, Boston, MA, 02115, United States of America,
sagar@coe.neu.edu
4 - Logistic Regression-Based Control Charts for Fault Identification
Jihoon Kang, Korea University, Anam-dong, Seongbuk-gu, Seoul,
Korea, Republic of, joker404@hanmail.net, Seoung Bum Kim
Co-Chair: Abe Zeid, Northeastern University, 360 Huntington Ave,
Boston, 02115, United States of America, zeid@coe.neu.edu
1 - A Bayesian Inventory Model using Real-time Condition
Monitoring Information
Jennifer Ryan, Associate Professor, RPI, Industrial and Systems
Engineering, 110 8th Street, Troy, NY, 12180,
United States of America, ryanj6@rpi.edu, Rong Li, Zhi Zeng
Identification of process variables that contribute to out-of-control signal has been
one of important problems in statistical process control. In the present study we
integrated a logistic regression algorithm with control chart techniques for fault
identification in multivariate process control. Simulation studies demonstrated the
accuracy and efficiency of the proposed fault identification method.
We consider a manufacturer who periodically replenishes inventory for a machine
part which is used simultaneously on a large set of geographically dispersed
machines. This part is subject to deterioration, which can be captured by condition
monitoring. We model the associated degradation signal using a Wiener process. In
such a setting, we show how real-time sensor data can be used to improve the
inventory management of spare parts.
■ WB30
Statistics/Quality Control I
2 - Application of Fuzzy Graph on Sensor Deployment Strategy for
Fault Diagnosis
Zhenhua Wu, Research Assistant, TAMU, 3902 College Main Street,
Apt.806, Bryan, TX, 77801, United States of America,
wuzhenhua34@tamu.edu, Sheng-jen Hsieh, Jianzhi Li
Contributed Session
Chair: Michael Wood, Principal Lecturer, University of Portsmouth,
Strategy and Business Systems, Richmond Building, Portland St,
Portsmouth, PO1 3DE, United Kingdom, michael.wood@port.ac.uk
1 - A New Monitoring Scheme for Various Types of Mean Shifts
Chang-Ho Chin, Assistant Professor, Kyung Hee University,
1 Seocheon-dong, Yongin-si, 446-701, Korea, Republic of,
chin@khu.ac.kr, Taek-Jin Jeong
I am sorry It only allows 500 characters, I can not submit my abstract. Is there any
way we can solve it? My email is: wuzhenhua34@tamu.edu Thank you!
3 - Short Term Performance of Condition Monitored Degrading
Manufacturing Systems
Saumil Ambani, University of Michigan, 1210 HH Dow, Ann Arbor,
MI, 48105, United States of America, sambani@umich.edu, Lin Li,
Jun Ni
The EWMA control chart is more sensitive to small mean shifts than to large ones as
opposed to the Shewhart control chart. The right selection of control charts to the
underlying process is directly linked with the timely detection of mean shifts. For
processes possibly with various types of mean shifts, we propose a control charting
scheme of selecting and applying a right control chart to the process. Simulation
results show the proposed scheme outperforms conventional ones.
Steady state performance of manufacturing systems has been studied for over 50
years, but its short term behavior remains relatively unexplored. In this
presentation, we focus on the development of an analytical model for predicting the
short term performance of a condition monitored degrading system. This approach
allows us to incorporate real time information from the plant floor, such as buffer
contents and condition of the machines, to make effective short term decisions.
2 - An Adaptive Sequential Methodology for n-Dimensional Quadratic
Response Surface Optimization
Adel Alaeddini, Wayne State University, Department of Industrial
Engineering, Detroit, MI, 48202, United States of America,
dz3027@wayne.edu, Kai Yang, Alper Murat
■ WB29
Despite their ability in modeling a wide range of process and product design, RSM
techniques are not the most effective methodologies for applications with limited
resources. In this paper, we develop an adaptive methodology for response surface
optimization (ASRSM) for expensive experiments with noisy data requiring high
design performance. We also show that in terms of both design optimality and
experimentation efficiency it compares favorably with optimal designs.
Joint Session QSR/ DM: Data Mining for
Process Monitoring
Sponsor: Quality, Statistics and Reliability/ Data Mining
Sponsored Session
3 - Modeling Data using Kalman Filtering: A Proposal for SPC
Andre Korzenowski, Prof. Ms., PPGEP/UFRGS, Av. Osvaldo Aranha,
99 - 5° andar, Porto Alegre, RS, 90.035-190, Brazil,
andre@korzenowski.com, Marcelo Portugal, Carla ten Caten
Chair: Myong Jeong, Rutgers University, 640 Bartholomew Road,
Piscataway, NJ, United States of America, mjeong@rci.rutgers.edu
1 - Hybrid Novelty Score-Based Control Charts for Multivariate
Process Monitoring
Gulanbaier Tuerhong, Korea University, Anam-dong, Seongbuk-gu,
Seoul, Korea, Republic of, gulambar@korea.ac.kr, Seoung Bum Kim
The aim of this paper is to compare forecasting in univariate time series models
applied in Statistical Process Control (SPC). A structural model in state space via
Kalman’s filtering and an ARIMA model with exogenous variables were fitted. The
modeling was applied in real data series of five different products in a plastic
production. The results obtained indicate that structural model had better
performance than ARIMA model when compared by RMSE.
We propose a new nonparametric multivariate control chart that can effectively
handle large amounts of complex data through integration of one of the one-class
classification algorithm with control chart techniques. Control limits of the proposed
chart are established based on a bootstrap method. Experimental results with
simulated data showed that the proposed control chart outperformed Hotelling’s T2
control charts.
4 - Problems with Statistical Methods in Management Research - and a
Few Solutions
Michael Wood, Principal Lecturer, University of Portsmouth, Strategy
and Business Systems, Richmond Building, Portland St, Portsmouth,
PO1 3DE, United Kingdom, michael.wood@port.ac.uk
2 - An Economic Design of the Integrated Process Control
Minjae Park, Rutgers University, 126 Montgomery St. Apt 2F,
Highland Park, NJ 08904, United States of America,
pminj88@gmail.com
A case study of a typical journal paper leads to three conclusions. (1) The value of a
statistical approach is seriously limited by various factors: e.g. difficulties of
generalizing to contexts other than the sample studied. (2) The conventional
hypothesis testing format makes results almost meaningless: instead, I suggest using
confidence levels for hypotheses - and suggest two ways of doing this (one a
bootstrap method on a spreadsheet). (3) The analysis should be far more userfriendly.
The economic cost model is developed for the integration of statistical process
control (SPC) and automatic process control (APC). SPC is used to detect special
causes by monitoring process performance. On the other hand, APC is used to
improve the process by an adjustment controller. Both are needed to effectively
keep processes close to target. The long run expected cost is also suggested as the
criteria to evaluate the performance of economic cost model.
395
WB31
■ WB31
■ WB32
Forecasting II
Computing Economic Equilibria
Contributed Session
Sponsored Session
Chair: Nitin Shenoy, Teaching Assistant, Texas Tech University, Texas Tech
Industrial Engineering Department, Lubbock, Tx, 79409-3061, United
States of America, nitin.shenoy@ttu.edu
1 - Wrong Response Functions: Their Detection and Implications
Steven Shugan, Professor, University of Florida, 2030 NW 24th
Avenue, Gainesville, FL, 32605, United States of America,
sms@ufl.edu
Chair: James Orlin, Professor, Massachusetts Institute of Technology, E53363, Cambridge, MA, 02139, United States of America, jorlin@mit.edu
1 - A New Convex Program for Fisher Markets and Convergence of
Proportional Response Dynamics
Nikhil Devanur, Microsoft Research, 1 Microsoft Way, Redmond,
WA, United States of America, nikdev@microsoft.com
This paper first explains why simple tests are unable to detect wrong response
functions. Next, the paper shows that wrong response functions use dampening and
inflated parameters to filter error variance to obtain better predictions. This
dampening is problematic when decisions require the correct response. Fortunately,
it is possible to detect dampening with specific tests for dampening. This paper
shows how to do that and demonstrates the effectives of those tests.
We give a new convex program that captures the equilibrium of spending constraint
utilities, thus resolving an open problem. The new program also demystifies the
convergence properties of “proportional response” dynamics: a simple, distributed
way to converge to market equilibria. We show that the proportional response
dynamics is equivalent to gradient descent on the new convex program, with KLdivergence instead of Euclidean distance.
2 - Role of Forecast Effort on Supply Chain Profitability Under Various
Information Sharing Scenarios
Linda (Xiaowei) Zhu, West Chester University of PA, 312A
Anderson, West Chester, United States of America,
xzhu@wcupa.edu, Xuemei Su, Samar Mukhopadhyay, Xiaohang Yue
2 - Equilibrium Computation for Low Dimensional Markets
Amin Saberi, Stanford University, Terman Engineering Building,
Room 317, Stanford, CA, 94305, United States of America,
saberi@stanford.edu
I will describe a model of markets in which every good has a value or desirability in
each of the k dimensions. The utility of every agent in a bundle is a function of the
values of the goods in that bundle in each dimension. In this model, I will present
polynomial-time approximation schemes for computing the equilibria when k is
bounded. Joint work with Costis Daskalakis
We analyze several forecast systems and their impact on forecast accuracy, forecast
costs and profit. Specifically, we consider a supplier who sells a product to a buyer
in a single selling season. Three different forecast systems, namely, Non-Information
Sharing, Information Sharing, and Supplier Forecasting were studied. We derive
optimal price and forecast accuracy level and discuss forecast variance and the
related forecast costs.
3 - Improved Algorithms for Computing Fisher’s Market Prices
James Orlin, Professor, Massachusetts Institute of Technology,
E53-363, Cambridge, MA, 02139, United States of America,
jorlin@mit.edu
3 - Unpacking the Future: A Nudge Towards Wider Interval Forecasts
Kriti Jain, Doctoral Student, INSEAD, 1, Ayer Rajah Avenue,
Singapore, Singapore, kriti.jain@insead.edu, Kanchan Mukherjee,
Neil Bearden, Anil Gaba
Irving Fisher developed a simple model of a market economy. Nevertheless, it is still
non-trivial to develop efficient algorithms for determining the market clearing
prices. We develop a combinatorial algorithm for computing the market equilibrium
that runs in O(n^4 log n) time, improving the previous best bound of O(n^8 log U).
With few exceptions, forecasters tend to underestimate uncertainty, for example, a
typical analyst’s 90% confidence intervals for future quantities will likely capture
only 50-60% of the actual realizations. Using a series of lab and field experiments,
we show that unpacking the distal future into intermediate more proximal futures
has a substantial effect on subjective forecasts. We refer to this phenomenon as the
time unpacking effect and show that it persists with expert judgments as well.
■ WB33
4 - The Welfare Implications of Carbon Taxes and Carbon Caps: A
Look at U.S. Households
Kara Kockelman, The University of Texas in Austin, ECJ Suite 6.9,
Austin, TX, United States of America, kkockelm@mail.utexas.edu,
Binny Paul, Sumala Tirumalachetty
Household expenditure and vehicle choice data are used here to anticipate the
economic impacts of energy taxes versus household-level carbon-emissions caps
(with trading) across different income classes. Translog utility models were
estimated and then maximized subject to money and carbon budget constraints.
U.S. trade accounts were used to infer the carbon footprints of 9 goods’ sectors, with
vehicle choice and fuel economy modeled in detail. Cap and trade was found less
regressive.
Chair: Jin Dong, IBM Research - China, Building 19 ZGC Software Park,
8 Dongbeiwang West Road, Beijing, 100193, China, dongjin@cn.ibm.com
1 - Supply Risk Management using Approximate
Dynamic Programming
Lei Zhao, Tsinghua University, Department of Industrial Engineering,
Tsinghua University, Beijing, 100084, China, lzhao@tsinghua.edu.cn,
Xiaobo Zhao, Weijun Ding, Jiarui Fang, Jan Fransoo
Business Analytics and Optimization Practices
Sponsored Session
5 - Propane Demand Modeling for Residential Sectors A Regression Analysis
Nitin Shenoy, Teaching Assistant, Texas Tech University, Texas Tech
Industrial Engineering Department, Lubbock, Tx, 79409-3061,
United States of America, nitin.shenoy@ttu.edu, Milton Smith
We consider a production system that is subject to failures at part suppliers.
Mitigation planning and emergent capacity can be used to hedge against the risk at
a higher cost. We model and solve the problem using finite-horizon approximate
dynamic programming.
2 - Mail Performance Measurement Study Process Improvements via
Business Analytics & Optimization at IBM
Hua Ni, IBM, 8000 Grainger Ct, Springfield, VA, 22153, United
States of America, huani@us.ibm.com, Christine Friesz
When winter space heating contributes significantly to the propane demand system;
it is useful, for forecasting purposes, to separate total demand system in to two
components: Large houses and Small houses. Examination of historical data
indicates that the propane demand depends largely on weather conditions.
Regression analysis techniques were used to show the combined effect of these
weather conditions on propane demand.
IBM conducts an ongoing measurement study of single-piece First-Class Mail service
performance for the United States Postal Service. In this talk, we will present recent
process improvement initiatives designed to strengthen the quality and operational
efficiency of the measurement study, which leveraged Business Analytics and
Optimization (BAO) methodologies such as optimization, simulation, and
predicative analytics. We will also share the challenges and lessons learned from
these efforts.
3 - Using Simulation in Global Supply Network Rationalization
Changrui Ren, IBM, Building 19 ZGC Software Park, 8 Dongbeiwang
WestRoad, Haidian District, Beijing, China, rencr@cn.ibm.com,
Xu Yang, Jin Dong, Qinhua Wang, Bing Shao, Miao He
This presentation will introduce a real case showing how simulation could be the
key enablement for a supply chain network rationalization project in the
pharmaceutical industry. An IBM tool - Supply Chain Process Modeler (SCPM) has
been applied in this project. Five major simulation scenarios are designed based on
the pain points the client has, and numerical results show that simulation has
addressed the key issues and provided the client accountable evaluation results for
decision-making.
396
WB36
■ WB35
4 - WISE-BPM: Accelerating Blueprint for Rollout Project in SAP
System Implementation
Qinhua Wang, IBM Research - China, Building19, Zhongguancun
Software Park, Beijing, 100193, China, wangqinh@cn.ibm.com,
Bing Shao, Miao He, Changrui Ren, Jin Dong
Advances in Anomalous Diffusion II
Sponsored Session
In SAP system implementation, business process model of a rollout project should
be conducted through localizing the global template. Simultaneously, global
template changes should be synchronized to all rollout projects, which causes
conflicts, information loss and duplication easily. WISE-BPM addresses this problem
through an additional version control system to rollout global template changes, a
localization flag and a mapping system to avoid information duplication and loss
respectively.
Chair: Iddo Eliazar, Professor, Holon Institute of Technology, P.O. Box
305, Holon, 58102, Israel, eliazar@post.tau.ac.il
1 - Anomalous Mixing and Reaction Induced by Spatially
Fractional Dispersion
David Benson, Colorado School of Mines, 1500 Illinois St., Golden,
CO, 80401, United States of America, dbenson@mines.edu,
Diogo Bolster, Tanguy Le Borgne, Marco Dentz
■ WB34
Long-range mass transfer changes the character of mixing of two fluids of different
chemical composition and the consequent chemical reaction. For mixing-limited
equilibrium reactions following the space-fractional Advection-Dispersion equation
(fADE), the scalar dissipation and global reaction rates decay as power-laws in time.
As opposed to the Fickian (local) transport model, local reaction rates are not zero
where the concentration has zero gradient.
C - Room 7, Level 3
Stochastic Optimization and Equilibrium Problems:
Analysis and Stochastic Approximation Algorithms
Sponsored Session
2 - Diffusive Processes Run with Non-linear Clocks: Complexity,
Ergodicity and Fractional F-P Equations
John Cushman, Professor, Purdue University, 550 Stadium Mall
Drive, West Lafayette, IN, 47906, United States of America,
75674.1670@compuserve.com
Chair: Uday Shanbhag, Asst. Professor, University of Illinois at Urbana
Champaign, Urbana, Il, United States of America, udaybag@illinois.edu
1 - Simulation-based Optimization in the Presence of Convexity
Eunji Lim, Assistant Professor, University of Miami, University of
Miami, Coral Gables, United States of America, lim@miami.edu
We study stochastic processes run with deterministic, but non-linear clocks. The
clock is used to stretch or compress the process. The clock does not change the
fractal dimension or complexity of the process. Ergodicity is analyzed for several
processes and compared to their classical analogs. Fokker-Planck equations for
several of the processes are derived and in some cases shown to possess fractional
derivatives. A number of misconceptions concerning power-law second moments
are discussed.
We consider the problem of computing a response surface when the underlying
function is known to be convex. We introduce a methodology that incorporates the
convexity into the function estimator. The proposed response surface estimator is
formulated as a quadratic program and exhibits convergence properties as a global
approximation to the true function. Numerical results will illustrate the convergence
behavior of the proposed estimator and its potential application to simulation
optimization.
3 - Influence of Anomalous Diffusion on the Robustness and Time
Evolution of Morphogen Gradients
Katja Lindenberg, Distinguished Professor, University of California,
San Diego, Department of Chemistry & Biochemistry, 9500 Gilman
Drive MC 0340, La Jolla, CA, 92093-0340, United States of America,
klindenberg@ucsd.edu, Santos B. Yuste, Enrique Abad
2 - Single Timescale Regularized Stochastic Approximation Schemes
for Monotone Stochastic Nash Games
Jayash Koshal, Department of Industrial & Enterprise Systems
Engineering, UIUC, 117 Transportation Building, 104 S. Mathews,
Urbana, 61801, United States of America, koshal1@illinois.edu,
Angelia Nedich, Uday Shanbhag
Crowded cellular environments are subdiffusive. The usual picture of morphogen
gradients evolving as a result of a source of normal diffusive particles (morphogens)
coupled to a degradation mechanism that removes them from the system must be
modified. We aim to investigate how subdiffusive motion of the morphogens affects
the evolution and robustness of the concentration profile against changes in the
degradation rate. We find interesting fluctuation buffering effects caused by
subdiffusion.
We consider the distributed computation of equilibria arising in monotone stochastic
Nash games over continuous strategy sets. We develop single timescale projectionbased stochastic approximation schemes for computing equilibria when the
associated gradient map is merely monotone and establish its global convergence. In
an extension where players choose their steplengths independently we claim the
convergence of the scheme if the deviation across their choices is suitably
constrained.
■ WB36
3 - On the Characterization of Solution Sets of Smooth and Nonsmooth
Stochastic Nash Games
Uma Ravat, Graduate Student, University Of Illinois, Urbana, IL,
61801, United States of America, ravat1@illinois.edu,
Uday Shanbhag
Education I
Contributed Session
Solution sets of deterministic Nash games over continuous strategy sets can be
characterized using variational analysis. A direct application of such results to
stochastic regimes is challenging as the expectation yields a far less tractable
nonlinear function. We develop an analytical framework to examine existence of
stochastic Nash equilibrium under general probability measures in possibly
nonsmooth regimes. We apply it to classes of Nash-Cournot games with risk and
stochastic constraints.
Chair: Thomas Groleau, Associate Professor of Business Administration,
Carthage College, 2001 Alford Park Drive, Kenosha, WI, 53140,
United States of America, tgroleau@carthage.edu
1 - Vertical Integration: Results From a Cross-Course
Student Collaboration
David Lewis, University of Massachusetts Lowell, 1 University
Avenue, College of Management, Lowell, MA, 01854,
United States of America, David_Lewis@uml.edu, Thomas Sloan
4 - Optimal Coverage of Rectangular Request Areas using Multiple
Rectangular Targets
Manish Bansal, PhD Student, Texas A&M University, 3131 TAMU,
bans1571@neo.tamu.edu, Kiavash Kianfar
We report the results of a cross-class project involving Sophomore-level students in
a Management Science (MS) class with Junior-level students in an Operations
Management (OM) class. The students formed virtual teams and developed a
simulation model of a call center. Results were strongly linked with the presence or
absence of a team champion.
We consider positioning k target rectangles on 2-dimensional plane to partially
cover a set of existing rectangular areas (requests) to maximize total coverage
reward. Applications include camera surveillance and imaging. We show this
problem is NP-hard and present a novel branch-and-bound algorithm over a
reduced solution space to solve the problem exactly. To our knowledge no
algorithm has been proposed before for this problem and our algorithm is memory
and performance efficient.
2 - Approach to Improve the Expense Efficiency of Research Capacity
of Universities
Jongwoun Youn, PhD Candidate, KUBS(Korea University Business
School), Anam-Dong, Seongbuk-Gu, Seoul, Korea, Seoul, Kr, 136701, Korea, Republic of, yjw333@korea.ac.kr, Kwang-Tae Park
Competitiveness of university can be expressed by education and research capacity.
Research capacity is an essential indicator for estimating the development of
university as well as that of our society. Thus, we want to propose the approach to
improve the expense efficiency of research capacity.
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3 - Teaching Decision Tree Classification using Microsoft Excel
Thaddeus Sim, Assistant Professor of Business Administration,
Le Moyne College, 1419 Salt Springs Road, Syracuse, NY, 13214,
United States of America, simtk@lemoyne.edu, George Kulick,
Kaan Ataman
4 - Call Centers with Hyperexponential Patience
Alex Roubos, VU University Amsterdam, Department of
Mathematics, De Boelelaan 1081A, Amsterdam, 1081 HV,
Netherlands, aroubos@few.vu.nl
We show that customers’ patience can be modeled by the hyperexponential
distribution; which allows an exact analysis. A framework is developed in order to
compute all kinds of practical service levels. This framework utilizes the recursive
relation between the queue lengths at successive service completion epochs. Our
approach shows overall better performance compared to current algorithms.
Moreover, the computation times are short and our approach can therefore readily
be applied in practice.
Data mining is the extraction of useful patterns from data to aid with decision
making, and decision makers are increasingly viewing data mining as an essential
analytical tool. Unfortunately, data mining does not get as much attention in the
traditional OR/MS classroom as other more popular areas. We discuss our
experiences in teaching a popular data mining method in an undergraduate OR/MS
elective course, and outline a procedure to implement the decision tree algorithm in
Microsoft Excel.
4 - A Different IE Teaching Experience: Active Learning
Ali Kefeli, PhD Candidate, North Carolina State University,
2717 Brigadoon Dr., Apt 24, Raleigh, NC, 27606,
United States of America, akefeli@ncsu.edu, Michael G. Kay
■ WB38
First-order Optimization Methods and
Their Applications
In this work, we take findings of a Felder and Brent (2008) and provide a critical
analysis of a senior level industrial engineering class at North Carolina State
University. We investigate each mistake laid out by Felder and Brent and argue how
avoiding them resulted in a better educational outcome. We provide sample
assessment tools such as class assignments and midterm questions, as well as active
learning exercises, technological tools and student evaluations.
(Joint Cluster ICS)
Sponsored Session
Chair: Zaiwen Wen, NSF Math Institutes’ postdoc, United States of
America, zw2109@columbia.edu
1 - Bundle-type Methods Uniformly Optimal for Smooth and
Non-smooth Convex Optimization
Guanghui Lan, Assistant Professor, University of Florida,
Department of Industrial and Systems Engineering, Gainesville, FL,
United States of America, glan@ise.ufl.edu
5 - Pre-Analytics with Cash for Clunkers
Thomas Groleau, Associate Professor of Business Administration,
Carthage College, 2001 Alford Park Drive, Kenosha, WI, 53140,
United States of America, tgroleau@carthage.edu
In summer 2009 nearly 700,000 new vehicles were purchased through the U.S.
government Cash Allowance Rebate System (CARS). The resulting dataset provides
a freely available pre-analytics training ground for a variety of classes. Using basic
desktop productivity software, students can practice data cleansing, data organizing,
and basic statistics on a very large dataset. Student can also prepare the data for
more detailed analysis with specialized geospatial or statistical software.
The study of Bundle or level-type methods has been focused on non-smooth convex
programming (CP) problems. In this talk we present new bundle-type methods
which are optimal, not only for non-smooth, but also for smooth convex
programming problems. Surprisingly, the optimal rates of convergence are obtained
without even requiring any smoothness information. We also demonstrate the
superior practical performance of these methods over existing optimal methods for
convex programming.
■ WB37
2 - Fast Splitting and Alternating Linearization Methods for
Convex Optimization
Shiqian Ma, Columbia University, 500 W. 120th Street, Mudd Blvd,
Room 313, New York, NY, 10027, United States of America,
sm2756@columbia.edu, Donald Goldfarb
Queueing Models of Call Centers
Sponsored Session
Chair: Itai Gurvich, Assistant Professor, Kellogg School of Management,
Northwestern University, 2001 Sheridan Rd., Evanston, IL, 60208,
United States of America, i-gurvich@kellogg.northwestern.edu
1 - Approximate Dynamic Programming Techniques for Skill-based
Routing in Call Centers
Sandjai Bhulai, VU University Amsterdam, Department of
Mathematics, Faculty of Sciences, Amsterdam, 1081 HV,
Netherlands, sbhulai@few.vu.nl, Dennis Roubos
In this talk, we present two classes of splitting and alternating direction methods for
which we can obtain iteration complexity bounds. The basic and accelerated
versions of these methods require 1/e and 1/e^(1/2) iterations to obtain an eoptimal solution, respectively. These complexity results are the first ones that have
been given for splitting and alternating direction type methods.
3 - A Unified Approach for Minimizing Composite Norms
Necdet Aybat, Columbia University, IEOR Department,
Columbia University, New York, NY, United States of America,
nsa2106@columbia.edu, Garud Iyengar
We consider the problem of dynamic multi-skill routing in call centers. We obtain
near optimal dynamic routing policies that are scalable with the size of the problem
instance and can be computed online. The algorithm is based on approximate
dynamic programming techniques. We compare the performance with
decomposition techniques. Numerical experiments demonstrate that our method
outperforms leading routing policies and has close to optimal performance.
FALC is a first-order augmented Lagrangian algorithm to solve
min{mu1|X|_*+mu2|C(X)-d|_1:A(X)=b},where X in R^{m*n},by inexactly solving a
sequence of problems.FALC converges to the optimal X_* if it is unique. For all e>0,
iterates are e-feasible, e-optimal in O(1/e) iterations.FALC can also solve:
min{mu1|X|_p+mu2|C(X)-d|_q+<R,X>:A(X)=b, F(X)-G is psd, |H(X)-h|_r <=s},with
the same convergence guarantees,where |.|_p can be nuclear, Frobenius or L2operator norm and q,r can be 1,2 or infinity.
2 - Comparing Erlang C and A for Modeling Real Call Centers
Tom Robbins, Assistant Professor, East Carolina University, 1006
Gemstone Circle, Winterville, 28590, United States of America,
Robbinst@ecu.edu, DJ Medeiros, Terry Harrison
■ WB39
Erlang C is a widely used model for call centers. Erlang C makes many assumptions
with one of the most problematic being no abandonment. Many authors have
recently advocated the use of the more complicated Erlang A model. We present the
results of a simulation study that compares the performance of these models over a
range of realistic call center conditions. We find that while the Erlang A model is
often more accurate, it is not always so. We also find the models have different
biases.
Advances in Mixed Integer Programming II
Sponsor: Optimization/Integer Programming
Sponsored Session
Chair: Jean-Philippe Richard, Associate Professor, University of Florida,
303 Weil Hall, P.O. Box 116595, Gainesville, FL, 32611,
United States of America, richard@ise.ufl.edu
1 - A Polyhedral Study of the Mixed Integer Cut
Steve Tyber, Research Assistant, Georgia Tech, 765 Ferst Drive, NW,
Atlanta, GA, 30332, United States of America,
steve.tyber@gatech.edu, Ellis Johnson
3 - Routing to Manage Resolution and Waiting Time in Call Centers
with Heterogeneous Servers
Yong-Pin Zhou, Michael G. Foster School of Business, Box 353200,
University of Washington, Seattle, WA, 98195-3200, United States of
America, yongpin@uw.edu, Kevin Ross, Geoff Ryder, Vijay Mehrotra
In many call centers, agents exhibit very different performance for the same call
type, where performance is defined by the average call handling time and the call
resolution probability. We explore strategies for determining call routing policies,
where call assignments are dynamically determined based on the specific attributes
of the agents and/or the current state of the system. We test several strategies using
data obtained from a financial service firm and present empirical results.
General purpose cutting planes have played a central role in modern IP solvers. In
practice, the Gomory mixed integer cut has proven to be among the most useful
general purpose cuts. One may obtain this inequality from the group relaxation of
an IP, which arises by relaxing non-negativity on the basic variables. We study the
mixed integer cut as a facet of the master cyclic group polyhedron and characterize
its extreme points and adjacent facets in this setting.
398
2 - A Probabilistic Comparison Between Split Cuts and Type 1
Triangle Cuts
Qie He, School of Industrial & Systems Engineering, Georgia
Institute of Technology, 765 Ferst Drive NW, Atlanta, GA, 30332,
United States of America, qie.he@gatech.edu, George L. Nemhauser,
Shabbir Ahmed
WB42
2 - Hybrid Genetic Algorithm for the Split Delivery Vehicle
Routing Problem
Joe Wilck, The University of Tennessee - Knoxville, 411 East
Stadium, Knoxville, TN, United States of America, jwilck@utk.edu,
Gautham Rajappa, Michael Vanderlan
The SDVRP allows customers to be assigned to multiple routes. A genetic algorithm
is presented where results from a construction heuristic are used to rank the
importance of certain node relationships. If nodes 2 and 9 appear on the same route
in many solutions, and those solutions have significantly lower distances when
compared to solutions where nodes 2 and 9 are not on the same route, then the
nodes 2 and 9 have a higher probability of being placed on the same route in future
generations.
The nontrivial facets for mixed-integer programs (MIP) with two rows and two
integer variables are split (or Gomory) cuts, three types of triangle cuts, and
quadrilateral cuts. This talk presents a probabilistic comparison of split and type 1
triangle cuts. Under a reasonable distribution of the problem parameters of the MIP,
we show that the average performance of a single split cut is better than a single
type 1 triangle cut in terms of dominance and volume cut off from the linear
relaxation.
3 - Solving Large Scale Dial-A-Ride Problem using a Two-Stage
Heuristic Based on Clustering-Routing
Taehyeong Kim, University of Maryland, Dept of Civil &
Environmental Eng, 1173 Glenn L. Martin Hall, College Park, MD,
20742, United States of America, tommykim@umd.edu, Ali Haghani
3 - A Polyhedral Study of the Triplet Fromulation for Single Row Facility
Layout Problem
Sujeevraja Sanjeevi, PhD Student, Texas A&M University, TAMU
3131, College Station, TX, 77843-3131, United States of America,
sujeevraja@tamu.edu, Kiavash Kianfar
In this paper, a static DARP model with time varying travel times and multiple
depots is formulated. Also, a heuristic methodology using two-stage is proposed to
solve this problem. At first stage, initial solution is constructed using clusteringrouting algorithm. And then, it is improved at next stage. The model is used to solve
a real world problem that is provided by the MTA in Baltimore, MD and the results
of implementing the model are compared with those of current system operations.
We present a polyhedral study of the triplet formulation for the Single Row Facility
Layout Problem, introduced by Amaral (Dis. App. Math., 2009). We show that this
polytope is of dimension n(n-1)(n-2)/3, where n is the number of facilities. We then
prove that several valid inequalities (VIs) proposed by Amaral are facet-defining.
This provides a theoretical support for the strength of the LP lower bounds obtained
by Amaral. We also present a generalized class of VIs that encompass Amaral’s VIs.
4 - Multi-depot, Multi-Destination, Mix-Fleet Vehicle Routing Problem
with Real-Life Constraints
Sam Thangiah, Professor, Slippery Rock University, 250 ATS,
Computer Science Department, Slippery Rock, PA, 16057,
United States of America, sam.thangiah@sru.edu, Joseph Forsythe
4 - Finding Good MIP Solutions by Restricted Tree Search
Menal Guzelsoy, Georgia Institute of Technology,
mguzelsoy@gatech.edu, George L. Nemhauser, Martin Savelsbergh
Starting with the branch-and-bound tree associated with the solution of a restricted
mixed integer program (MIP), i.e., a MIP in which some variables are fixed, we
expand certain nodes of the search tree by using dual information to selectively free
previously fixed variables in the hope of quickly finding improved solutions.
This paper presents a real-life multi depot, multi-destination, mix-fleet vehicle
routing problem with 1200 pickup locations, 2000 customers and 60 vehicles. The
precise distances between pickup locations are obtained using digitized road maps
instead of Euclidean distance. Heuristics for solving the problem and results for the
real-life data set are reported.
■ WB40
■
Panel Discussion: COIN-OR Technology Forum
WB42
Cluster: John Forrest-fest | COIN-OR 10th (Joint Cluster Computing)
Invited Session
Computational Optimization and Applications II
(Joint Cluster ICS)
Sponsored Session
Moderator: Ted Ralphs, Associate Professor, Lehigh University, 200 West
Packer Avenue, Bethlehem, PA, 18015, United States of America,
ted@lehigh.edu
1 - Panel Discussion: COIN-OR Technology Forum
Panelists: Ted Ralphs, Associate Professor, Lehigh University, 200
West Packer Avenue, Bethlehem, PA, 18015, United States of
America, ted@lehigh.edu, Lou Hafer, Simon Fraser University,
Burnaby BC V5A 1S6, Canada, lou@cs.sfu.ca, William Hart, Sandia
National Laboratories, PO Box 5800, Albuquerque NM, United States
of America, wehart@sandia.gov, Kipp Martin, University of Chicago,
5807 South Woodlawn, Chicago IL 60637, United States of America,
kmartin@chicagobooth.edu
Chair: Ali Ekici, Assistant Professor, University of Houston, Department of
Industrial Engineering, E221A Engineering Building 2, Houston, TX,
77204, United States of America, aekici@Central.UH.EDU
1 - On the Parallel Computation of Individual Penalties in
Scheduling Jobs
Irinel Dragan, Professor Emeritus of Mathematics, University of
Texas at Arlington, U.T.Arlington, Mathematics, Arlington, TX,
76019-0408, United States of America, dragan@uta.edu
Following up on last year’s successful forum, this panel discussion will be an
opportunity for users and developers of COIN-OR software to discuss recent and
future developments within COIN-OR. If you want to get involved, provide
feedback, or just learn about COIN-OR, please join us!
For scheduling n jobs on a single machine, with a common due date. and given
weights, we want to find a schedule which minimizes the total penalty. We build a
scheduling game and we propose to compute in parallel the individual penalties as
the Shapley Value expressed by means of the Average per capita formula
(Dragan,1992).
■ WB41
2 - Experience in Developing Heuristic Algorithms to Solve Large-scale
Non-convex NLP Problem
Vladimir Krichtal, Senior Development Engineer, Transpower NZ, 96
The Terrace, P.O. Box 1021, Wellington, New Zealand,
Vladimir.Krichtal@transpower.co.nz, Conrad Edwards
Vehicle Routing II
Transpower, as the New Zealand power system operator, uses an LP dispatch and
pricing model. The model is derived from a non-convex NLP one, with quadratic
circuit losses approximated by piece-wise linear functions. Sometimes the solver
does not solve the resulting LP model correctly. The types of incorrect solutions are
identified. Some of these incorrect solutions are prevented via market rule changes.
Other can be fixed using heuristic iterative MIP algorithms.
Contributed Session
Chair: Sam Thangiah, Professor, Slippery Rock University, 250 ATS,
Computer Science Department, Slippery Rock, PA, 16057,
United States of America, sam.thangiah@sru.edu
1 - Backhaul Vehicle Routing Problem with Time Constraint
Yuanyuan Dong, Southern Methodist University, P.O. Box 750123,
Dallas, TX, 75275-0123, United States of America,
njdyy03@gmail.com, Junfang Yu
3 - Cutting Stock Problem with Setup Costs
Ali Ekici, Assistant Professor, University of Houston, Department of
Industrial Engineering, E221A Engineering Building 2, Houston, TX,
77204, United States of America, aekici@Central.UH.EDU,
Azadeh Mobasher
A backhaul vehicle routing problem has been studied in which maximum profit is
desired during backhaul trip but travel time is constrained. A heuristic algorithm,
adapted from genetic algorithm, has been developed and implemented for the
problem. Empirical study has been performed to show the efficiency and
effectiveness of the algorithm.
We study the weighted cutting stock problem which is a more general version of the
well-known cutting stock problem. The objective in weighted cutting stock problem
is to minimize total production cost including both waste and setup costs. Since the
problem is NP-hard, we develop heuristic algorithms to find good solutions and test
their effectiveness on randomly generated instances.
399
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■ WB44
2 - A Systems Approach to Reducing Medication Errors
Niquelle Brown, Georgia Institute of Technology, Atlanta, GA,
United States of America, niquelle.brown@gatech.edu,
Deniz Cinalioglu, Hyo Jung Kang, Eva Lee
Appointment Scheduling in Healthcare
Medication errors pose significant impact on patient safety and quality of care. In
this study, a systems perspective is adopted in developing simulation-optimization
models for describing the medication work flow in a pediatric setting. The system
allows for derivation and validation of effective intervention strategies for error
mitigation. This work is joint with Children’s HealthCare of Atlanta.
Sponsored Session
Chair: Serhan Ziya, University of North Carolina, 356 Hanes Hall
CB# 3260, Chapel Hill, NC, 27599, United States of America,
ziya@email.unc.edu
3 - Optimizing Emergency Department Workflow
Anna Yang, Georgia Institute of Technology, Atlanta, GA,
United States of America, anna.yangyang@gatech.edu, Eva Lee
Co-Chair: Nan Liu, Mailman School of Public Health, Columbia
University, 600 W 168th ST, 6th Floor, New York, NY, 10032, United
States of America, nl2320@columbia.edu
1 - A Comparison of Traditional and Open-access Appointmentscheduling Policies
Rachel Chen, University of California at Davis, Graduate School of
Management, Davis, CA, 95616, United States of America,
rachen@ucdavis.edu, Lawrence Robinson
In this work, we study the ED workflow of a large public hospital, design a
computer model that can capture the current processes, identify major bottlenecks,
and develop effective intervention and recommendation. The study and
recommended systems intervention will enable hospital policy makers to transform
existing ED processes so as to improve quality of care, timeliness of care, efficiency,
and possible financial gains and investment. This work is joint with Grady Health
Systems.
Under traditional scheduling, patients are booked in advance, but may not show up.
Under open-access scheduling, a random number of patients call in the morning to
make an appointment for that same day. Thus under either policy the number of
patient arrivals will be random, for different reasons. We find that the open-access
schedule in general outperforms the traditional schedule, except when patient
waiting time is held in little regard or when no-show probability is small.
4 - Evaluating and Building a Decision Support System for
Trauma Patients
Oguzhan Ozlu, Georgia Institute of Technology, Atlanta, GA,
United States of America, aozlu3@isye.gatech.edu, Eva Lee
Trauma patients demand rapid transportation to the most suitable hospital for
treatment where timeliness of care, and quality of care are of paramount
importance. Some critical objectives include maximizing the best treatment outcome
for trauma patients as well as optimal/smart usage of available regional resources. In
this talk, we present our work with Georgia Trauma Commission on optimal care
delivery aiming to improve trauma care across the Georgia State.
2 - Adaptive Appointment Systems with Patient Preferences
Wen-Ya Wang, University of Minnesota, 111 Church St SE,
Minneapolis, MN, 55455, United States of America,
wenya@ie.umn.edu, Diwakar Gupta
We propose a framework for the design of the next generation of appointment
systems that dynamically learn and update patients’ preferences, and use this
information to improve booking decisions. Analytical results leading to a partial
characterization of an optimal booking policy are presented. Examples show that
heuristic decision rules, based on this characterization, perform well and reveal
insights about tradeoffs among a variety of performance metrics important to clinic
managers.
■ WB46
Game-Theoretic Applications in Healthcare I
3 - Controlling Demand for Appointment-based Services in the
Presence of No-show Customers
Nan Liu, Mailman School of Public Health, Columbia University,
600 W 168th ST, 6th Floor, New York, NY, 10032,
United States of America, nl2320@columbia.edu, Serhan Ziya
Sponsored Session
Customer no-shows is a major problem for many service systems that work with
appointments. In this talk, we model the scheduled appointments as a single-server
queue and investigate how to maximize system throughput taking into account
waiting time dependent no-shows. We also study how to adjust the system design
in response to changes in customer no-show behavior. Both analytical and
numerical results will be presented.
Co-Chair: Reza Yaesoubi, Post-Doctoral Research Fellow,
Harvard Medical School, 641 Huntingtone Ave., Boston, MA, 02115,
United States of America, reza.yaesoubi@gmail.com
1 - Decentralized Resource Allocation to Control an Epidemic:
A Game Theoretic Approach
Shouqiang Wang, PhD Student, Fuqua School of Business, Duke
University, 1 Towerview Dr., Durham, NC, 27707, United States of
America, sw55@duke.edu, Peng Sun, Francis de Vericourt
Chair: Murat Kurt, PhD Student, University of Pittsburgh, Department of
Industrial Engineering, 3700 O’Hara Street, 1048 Benedum Hall,
Pittsburgh, PA, 15217, United States of America, muk7@pitt.edu
■ WB45
This paper examines how two countries would allocate resources at the onset of an
epidemic when they seek to protect their own populations. We model this situation
as a game between selfish countries, where players strategically allocate their
resources in order to minimize the total number of infected individuals in their
respective populations during the epidemic. We also consider possible extensions.
Modeling and Optimizing Quality of Care and Efficiency
of Delivery
Sponsored Session
2 - Characterization of Payoff Efficient Equilibria in Prearranged Paired
Kidney Exchanges
Murat Kurt, PhD Student, University of Pittsburgh, Department of
Pittsburgh, PA, 15217, United States of America, muk7@pitt.edu,
Mark S. Roberts, Andrew J. Schaefer, M. Utku Unver
Chair: Eva Lee, Professor & Director, Georgia Institute of Technology,
Center for Operations Research in Medici, Industrial & Systems
Engineeriing, Altanta, GA, 30332-0205, United States of America,
eva.lee@gatech.edu
1 - Quantifying Reductions in Variability of Intraoperative Time From
Meta-analysis of Trial Results
Franklin Dexter, Professor, University of Iowa, Department of
Anesthesia, 6JCP, Iowa City, IA, 52242, United States of America,
franklin-dexter@uiowa.edu
We consider a non-zero sum stochastic game formulation to model the transplant
timing decisions in a prearranged paired kidney exchange. Due to trade-off between
the payoff efficiency and the stability of the equilibria, we characterize the socially
efficient stable equilibrium as an optimal solution to an MIP. For large-scale
problems, based on single-controller MDP models, we develop an iterative best
response algorithm. We present computational results based on clinical data.
Electronic medical record data were used to facilitate meta-analysis of randomized
clinical trials. For interventions affecting anesthetic durations, usually there are
many (> 20) clinical trials each with small N (<20). Analyzing anesthesia EMR data,
probability distributions of extubation times were Weibull. Choice of drug did not
influence Weibull shape parameters. Appropriate Bayesian and non-Bayesian
random effect meta-analyses were then used to quantify reduction in time
variability.
3 - Coordinating Contracts in a Preventive Health Care System Under
Capacity Restrictions
Reza Yaesoubi, Post-Doctoral Research Fellow, Harvard Medical
School, 641 Huntingtone Ave., Boston, MA, 02115,
United States of America, reza.yaesoubi@gmail.com, Stephen Roberts
We consider a health care system consisting of two noncooperative parties: a health
purchaser and a health provider. The health provider, bounded by capacity,
determines the type of patients who should undergo a preventive medical
intervention, and then gets reimbursed by the health purchaser according to a
contract. We determine the contracts that coordinate this system; i.e., the contracts
that allow both parties to maximize their objective functions while maximizing the
population’s welfare.
400
WB50
■ WB49
4 - Influenza Vaccine Supply Chain: Role of Consumption Externality
and Yield Uncertainty
Kenan Arifoglu, PhD Student, Northwestern University, 2145
Sheridan Road, Room C 210, Evanston, IL, 60208, United States of
America, kenanarifoglu2011@u.northwestern.edu, Sarang Deo,
Seyed Iravani
Systems Analysis and Design
Sponsored Session
We consider the inefficiency in flu vaccine supply chain and study the impact of two
critical factors: yield uncertainty (supply side) and self-interested consumers
(demand side). Contrary to previous economic models, we find that consumers may
demand more vaccinations than is socially optimal when they jointly consider the
availability and infection externalities. We study two partially-centralized supply
chains to investigate the benefits of government interventions on demand and
supply side.
Chair: Vijay Khatri, Indiana University, 1309 E. 10th Street, BU 560F,
Bloomington, IN, 47405, United States of America, vkhatri@indiana.edu
Co-Chair: Jeffrey Parsons, jeffreyp@mun.ca
1 - A Cognitive Perspective on Developing and Interpreting
Conceptual Models
Palash Bera, Assistant Professor, Texas A&M InternationalUniversity,
5201, University Blvd., Laredo, TX, 78041, United States of America,
palash.bera@tamiu.edu
■ WB47
Conceptual models are often used to document features of the domain to be
reflected in the Information Systems. Developing and interpreting conceptual
models can be considered as cognitive tasks performed by modelers. In a laboratory
setting, this study contrasts the cognitive difficulties faced by two groups of
modelers- one who develops the models and the other who interprets the same
models. The results indicate that the cognitive difficulties faced by the groups are of
different nature.
Project Scheduling and Risk Management
Invited Session
Chair: Richard Wendell, Professor, Katz Graduate School of Business,
University of Pittsburgh, Pittsburgh, PA, 15260, United States of America,
wendell@katz.pitt.edu
2 - Business Informational Sabotage: An Exploration into Incidence
Rates and Causes
John Erickson, University of Nebraska at Omaha, College of
Business, 6001 Dodge Street, Omaha, NE, 68182, United States of
America, johnerickson@mail.unomaha.edu, George Gresham,
John Hafer
Co-Chair: Timothy Lowe, Professor, Tippie College of Business,
University of Iowa, Iowa City, IA, United States of America,
timothy-lowe@uiowa.edu
1 - New Product Design and Pricing in a Duopoly Market with
Forward-looking Consumers
Ted Klastorin, Burlington Northern/Burlington Resources Professor,
Department of Information Systems & Operations Mgt, Michael G
Foster School of Business, University of Washington, Seattle, WA,
98195-3200, United States of America, tedk@u.washington.edu,
Aysun Ozler, Yong-Pin Zhou
This study represents an exploratory effort into the occurrence rates of nineteen
types of organizational information sabotage, moral attitudes towards the acts and
the saboteurs. Roughly 40% of the respondents indicated awareness of sabotage and
up to 31% admitted committing one/some acts of sabotage. Demographic variables
were tested for significance.
3 - Experiments in Paired Software Development
Radha Mahapatra, Associate Professor, University of Texas at
Arlington, 701 S. West St., Arlington, TX, 76019-0437,
United States of America, mahapatra@uta.edu, Sridhar Nerur,
VenuGopal Balijepally, George Mangalaraj
We study the introduction of a new product into a durable goods duopoly market.
In our model, an innovator firm begins to develop a product; after a random time
period, information about this product leaks and an imitator firm begins to develop
a competing product. Consumers are forward looking and make purchases based on
the available product and their expectations on future products. We derive
implications for both profit-maximizing firms with respect to the design and pricing
of the products.
A core practice in recently popularized agile software development methods is
paired development, where two developers work together to jointly design and
develop application systems. We have conducted a series of experiments to
understand the efficacy of paired development vis-á-vis the traditional practice of
software development by developers working individually. Findings from these
experiments will be presented.
2 - Planning Stochastic Projects Under the Threat of a Disruptive Event
Gary Mitchell, Assistant Professor, Pamplin School of Business
Administration, University of Portland, 5000 N. Willamette Blvd,
Portland, OR, 97035, United States of America, mitchelg@up.edu,
Ted Klastorin, Issariya Sirichakwal
■ WB50
We consider the issue of planning a stochastic project when there is a threat of an
exogenous disruptive event that may stop work on one or more tasks (possibly the
entire project). Our goal is to minimize expected total project costs, including
resource costs, overhead/indirect costs, and penalty costs. We analyze a model to
determine when the project manager should take proactive steps during the
planning phase or wait and take contingent actions after a disruption occurs.
Information Systems I
Contributed Session
Chair: Zsolt Ugray, Associate Professor, USU, 3515 Old Main Hill, Logan,
United States of America, Zsolt.Ugray@usu.edu
1 - Bundling of Information Sources using the Value of Information
Pantea Alirezazadeh, PhD Student, University of Connecticut, 2100
Hillside rd, Unit 1041, Storrs, CT, 06269, United States of America,
pantea.alirezazadeh@business.uconn.edu, Fidan Boylu, Ram Gopal
3 - Agility in Projects - Theoretical and Computational Results
Karolina Glowacka, Assistant Professor, Stevens Institute of
Technology, Howe School of Technology Management, Hoboken, NJ,
07030, United States of America, kglowack@stevens.edu, Richard
Wendell, Timothy Lowe
In this research we show that a lack of agility can be a significant factor in project
delays. We characterize the concept of agility in projects, show how agility can have
a significant impact on the likelihood of achieving a target-time for a project, and
give some general properties on agility with respect to a project’s structure. We also
discuss how and where to build agility into key project activities.
We present a method for acquiring information from multiple information sources
with different reliabilities based on the incremental value of information. We
evaluate the value of information that can be provided by third-party data providers
and measure the value of different combinations of information sources based on
their contribution to expected utility and provide heuristic solutions to select an
optimal combination of these information sources.
4 - Integration of Project Management and Software Development
Processes in a Complex Project
Laura Anderson, Manager, Advanced Estimating & Infrastructure
Solutions, IBM Research - Almaden, 650 Harry Road, San Jose, CA,
95120, United States of America, laurac@almaden.ibm.com,
Ruoyi Zhou
2 - Understanding Time Inconsistent Preferences in Real Options
Based it Investment Justification
Ram Kumar, UNC- Charlotte, 9201 University City Blvd, Charlotte,
NC, United States of America, rlkumar@uncc.edu,
Sarah Khan
The literature on the use of Real Options in IT (and other) investment justification
assumes that decison makers will be able to exercise options optimallly. However, in
practice, decision makers can have time inconsistent preferences. The effects of
these preferences on the use of Real Options Analysis is analyzed. This analysis has
important implications for decison makers.
Project management continues to increase in complexity, with special challenges
due to agile methodologies and geographically dispersed teams. We describe our
experience in software project management for a medium sized research and
development project using IBM’s Rational Jazz™. We discuss the observed
advantages of Jazz in systematizing the overall process, with narrative observations,
quantitative measurements, and objective measures of the value of such a project
management system.
401
WB51
■ WB52
3 - Multicriteria Model for Selecting Information Systems Based on the
PROMETHEE Method
Jônatas Almeida, Federal University of Pernambuco, Recife-PE,
Brazil, jonatasaa@yahoo.com.br, Ana Paula Costa, Adiel Almeida
Assessing Terrorism Probabilities and All-Hazards Risk
in the U.S. Department of Homeland Security
This paper discusses the importance of the process of selecting Information Systems
(ISs) integrated with an IS planning methodology. A model which integrates an
adapted version of an IS planning methodology called Business System Planning
(BSP) and the multicriteria method PROMETHEE II is presented. As a contribution,
this paper identifies the need for ISs to start from the company’s strategic vision,
including how value is to be added to the business, considering aspects for the
organization.
Cluster: Homeland Security and Defense
Invited Session
Chair: Steve Bennett, Asst. Director, Risk Analytics Division, Office of
Risk Management and Analysis, U.S. Department of Homeland Security,
Washington, DC, 20528, United States of America, steve.bennett@dhs.gov
1 - Relative Probabilities of Terrorist Attacks: Rational Adversaries with
Uncertain Value Tradeoffs
Evan Levine, DHS Office of Risk Management and Analysis,
2929 Connecticut Ave NW, Apt 709, Washington, DC, 20008,
United States of America, evan.levine@dhs.gov
4 - Franchisee Attitudes Toward the Adoption of Advanced Internet
Technologies and Innovations
Zsolt Ugray, Associate Professor, USU, 3515 Old Main Hill, Logan,
United States of America, Zsolt.Ugray@usu.edu, Kelley O’Reilly
We present findings from a case study exploring franchisees’ attitudes and
perceptions of using advanced Internet technologies and innovations. We illustrate
that the dual role of owner-operators, in which they are both decision makers and
users of technologies, provides a dichotomy of perspectives that yield insights into
aspects of business leadership, customer service, and operational proficiency.
Many analyses conducted to inform counterterrorism decisions depend on estimates
of the relative probabilities of different attack types. We describe a method of using
uncertainty in utility function value tradeoffs to model the adversary’s decision
process and solve for the relative probabilities of attacks in closed form. The process
we describe is an extension of value-focused thinking, and is suitable for application
outside of counterterrorism, including general business decision-making.
■ WB51
2 - Informing All-hazards Decision-making at the U.S. DHS:
Constructing an Appropriate Scenario Set
Julie Waters, Risk Analyst, Office of Risk Management and Analysis,
U.S. Department of Homeland Security, Washington, DC, 20528,
United States of America, julie.waters@dhs.gov, Evan Levine,
Steve Bennett
Analyses for Rotary Wing Aircraft
Sponsored Session
The Homeland Security National Risk Assessment (HSNRA) methodology, developed
by DHS, uses an order-of-magnitude estimation technique to quantify the dominant
risks across the disparate hazards confronted by the Nation. In this presentation, we
discuss how the space of possible events relevant to homeland security is discretized
into scenarios that form the units of analysis for frequency and consequence
elicitation and the process by which dominant scenarios are identified.
Chair: Caolionn O’Connell, Institute for Defense Analyses, 4850 Mark
Center Drive, Alexandria, VA, 22311, United States of America,
coconnel@ida.org
1 - Rotary Wing Aircraft Capacity for Operations in Afghanistan
Matthew Grund, Research Analyst, CNA, 4825 Mark Center Drive,
Alexandria, VA, 22311, United States of America, grundm@cna.org,
Greg Cox
3 - Eliciting Probabilities From the Intel Community to Support
Terrorism Risk Assessments at U.S. DHS
Natasha Hawkins, Risk Analyst, U.S. Department of Homeland
Security, Washington, DC, 20528, United States of America,
natasha.hawkins@dhs.gov, Tony Cheesebrough, Steve Bennett
Senior leaders in the Department of Defense have expressed concern that there is
insufficient rotary wing capacity in Afghanistan to effectively carry out the required
missions. Our work broadly explores three ways of increasing rotary wing capacity
in Afghanistan: increasing the number of aircraft in theater, increasing the hours
flown by aircraft already in theater, and increasing the efficiency of flight hours
already being flown by aircraft in Afghanistan.
Probability elicitations for terrorism involve engaging intelligence community
experts who generally communicate threat judgments in qualitative terms. This
presentation will discuss challenges and opportunities in applying expert elicitation
methods to the elicitation of intelligence information in DHS and provide an
opportunity for the OR/MS community to provide input and suggestions for
improvement and enhancement.
2 - Utility Assessment of Rotary Wing Aircraft
Dana Paterson, Senior Analyst, Naval Air Systems Command,
Bldg 2109, Room S211, Patuxent River, MD, 20670,
United States of America, dana.paterson@navy.mil
4 - RAPID: Supporting Risk-informed Strategic Policy and Resource
Allocation Decisions at the U.S. DHS
Debra Elkins, Section Chief, Risk Assessments and Analysis, U.S.
Department of Homeland Security, U.S. Department of Homeland
Security, Washington, DC, 20528, United States of America,
debra.elkins@dhs.gov, Steve Bennett, Tony Cheesebrough,
Natasha Hawkins
Decision makers faced with making a choice among a finite set of rotary-wing
aircraft, aircraft designs or aircraft concepts must have information products
describing the utility of each member of the set. This briefing is a description of a
senior analyst’s method beginning with identification of the decision to be made and
ending with an exposition of his preferred method for describing the decision space
for the decision maker.
3 - A Forensic Analysis of Cost Growth in Rotary Wing Programs
Caolionn O’Connell, Institute for Defense Analyses, 4850 Mark
Center Drive, Alexandria, VA, 22311, United States of America,
coconnel@ida.org
The Risk Assessment Process for Informed Decision-making (RAPID) is a risk
assessment conducted within the DHS Office of Risk Management and Analysis that
supports strategic policy and budgetary decision-making across the U.S. Department
of Homeland Security. This presentation will describe the technical risk analysis
methodologies used in RAPID and provide an opportunity for the OR/MS
community to provide input and suggestions for improvement and enhancement.
An analysis of cost growth in rotary wing (RW) programs and how it compares to
other major defense acquisition programs (MDAPs). The brief will also include a
discussion of possible root causes for RW cost growth and a suggested cost
estimating methodology for future programs.
4 - Army Aviation Force Structure
Steven Stoddard, US Army, Burke, VA, United States of America,
steven.stoddard@us.army.mil
The Army has the responsibility to provide manned, trained, and equipped units to
support operations. We explain how the Army manages the supply of helicopter
units to meet as much demand as possible. We answer three questions: 1.
What happens if the Army adds more helicopters? 2. What happens if the Army
uses its helicopter units more often? 3. What happens if the Army alters its active reserve mix?
402
■ WB53
WB55
2 - Cost-Optimal Reinspection Plans
Hadi Zaklouta, Graduate Student Researcher, MIT Materials Systems
Laboratory, 292 Main Street, E38-435, Cambridge, MA, 02139,
United States of America, zaklouta@mit.edu, Randolph Kirchain,
Richard Roth
Operations/Marketing Interface I
Contributed Session
This paper compares single and double inspection plans effect on cost and quality. A
cost model is proposed that accounts for appraisal and internal/external failure
costs. All units are tested with one or two tests. In plan RR, rejects are retested and
replaced after rejection. In plan AR, accepts are retested and rejects replaced. Nonconformance rate and test error rates are known. The AR plan is best for high
warranty/scrap cost ratio; the RR plan for low; a single test plan otherwise.
Chair: Baokun Li, Dr., Southwestern University of Finance and
Economics, 555 Liutai Ave, Wenjiang District, Chengdu, 611130, China,
flyinghorse1967@yahoo.com
1 - Market-based Joint Decisions on Price, Delivery Time, Service
Level, and Supplier Selection
Li Qian, South Dakota State University, Solberg Hall 115B,
Brookings, 57006, United States of America, li.qian@sdstate.edu
3 - Learning as a Driver Technology Choice Decisions in Manufacturing
Thomas Rand-Nash, Doctoral Candidate, Massachusetts Institute of
Technology Materials Systems Laboratory, 77 Massachusetts Avenue,
Cambridge, MA, 02139, United States of America, trand@mit.edu
This paper models the demand as a linear or log-linear function of attributes
including price, guaranteed delivery time, and service level. With stochastic delivery
time, the service level is not always binding at the minimal value reserved by the
manager or the market, as assumed in most literature. A market-oriented approach
for supplier selection or investment is proposed in consideration of operation
performances in cost, delivery time, service level, and/or quality in an integrated
manner.
This work explores process technology decision making in the presence of learning
effects in manufacturing, and hopes to characterize the conditions under which
learning-related production cost effects impact technology choice decision making.
Relevant factors considered include learning rates, production volume as a function
of demand, market structure, and budget constraints.
2 - Cooperative Advertising in a Dynamic Durable Goods Supply Chain
Anshuman Chutani, UT Dallas, School of Management, SM 30,
Richardson, TX, 75080, United States of America,
anshuman.chutani@student.utdallas.edu, Suresh Sethi
4 - Shifting Grounds: How Industry Emergence Changes the
Effectiveness of Knowledge Creation Strategies
Sebastian Fixson, Babson College, Babson Park, MA,
United States of America, sfixson@babson.edu, Won Hee Lee
We analyze dynamic advertising and pricing policies in a durable goods supply chain
with co-operative advertising. We consider a stackelberg game where manufacturer
announces the wholesale price and its share in the retailer’s advertising
expenditure. The retailer responds with its optimal advertising and pricing policies.
The sales dynamics follows the model suggested by Sethi, Prasad and He (2008). We
analyze two different demand specifications, linear and iso-elastic.
The knowledge management literature has identified various aspects, advantageous
and disadvantageous, of both inward-looking and outward-looking knowledge
creation strategies. With a longitudinal empirical study we explore the dynamics of
firms’ knowledge creation strategies during the period of industry emergence. We
find that the emergence of an industry changes the effectiveness of the different
knowledge creation strategies.
3 - Can We All Get Along? Incentive Contracts to Bridge the Marketing
and Operations Divide
Kinshuk Jerath, Assistant Professor, Carnegie Mellon University,
5000 Forbes Ave, Pittsburgh, PA, 15213, United States of America,
kinshuk@cmu.edu
■ WB55
Sustainability and NPD
The marketing and operations management arms in a firm must work in
coordination. However, a major source of conflict is that marketing compensation is
usually heavily weighted towards sales whereas operations compensation is usually
heavily weighted towards expense reduction. In this paper, we invoke agency
theory to determine compensation plans for sales and operations managers to
coordinate their activities in the best interests of the firm.
Sponsored Session
Chair: Cheryl Druehl, Assistant Professor, George Mason University,
4400 University Dr, MS 5F4, Fairfax, VA, 22030, United States of
America, cdruehl@gmu.edu
1 - New Business Models to Enable Clean and Renewable Generation
in the Electric Power Industry
Edward Anderson, Associate Professor, University of Texas,
1 University Station B6500, Austin, TX, 78733, United States of
America, Edward.Anderson@mccombs.utexas.edu, Geoffrey Parker
4 - Computing Reasonable Allocations in Coalition Games
Baokun Li, Dr., Southwestern University of Finance and Economics,
555 Liutai Ave, Wenjiang District, Chengdu, 611130, China,
flyinghorse1967@yahoo.com
We introduce a new kind of coalition gain allocation, Proportion Allocation, which
is inspired from the Coarsening at Random mechanism in statistics. Based on the
Proportion Allocation and traditional Shapley value, a reasonable class of allocations
is dened and related algorithm is given for calculating them. Besides, a simulated
annealing method is constructed to solve for the stable allocation, nucleolus, for
coalition games.
Over the coming decades, electric power companies must transform their business
models to accommodate the smart grid and growing demand for clean renewable
energy. Many researchers are examining aspects of this problem, such as power
companies’ infrastructure portfolios, consumer behavior, pricing structures, etc. To
complement this analysis, we build and analyze a top-down systems model of a
typical power company and its market “ecosystem” using the system dynamics
methodology.
■ WB54
2 - Does “To Go Green” Translate into Profitability?
Asoo Vakharia, Professor, University of Florida, Department of ISOM,
Gainesville, FL, 32611-7169, United States of America,
asoo.vakharia@warrington.ufl.edu, Arda Yenipazarli
Characterizing Uncertainty and Learning for
Technology Choice Decisions
Consumers are frequently integrating “green” product attributes when making
purchasing decisions. We propose a firm level analytical model to enable decisions
on whether to upgrade the “green” content of an existing product, replace the
existing product with a “green” product, or provide a portfolio of an existing and
“green” product.
Sponsored Session
Chair: Thomas Rand-Nash, Doctoral Candidate, Massachusetts Institute of
Technology Materials Systems Laboratory, 77 Massachusetts Avenue,
Cambridge, MA, 02139, United States of America, trand@mit.edu
1 - Learning-Derived Cost Evolution in Materials Selection
Trisha Montalbo, MIT, 77 Massachusetts Ave, E38-420, Cambridge,
United States of America, trisha@mit.edu, Richard Roth
3 - Reviving the Electric Car Movement: Developing Green
Infrastructure for Sustainable Transportation
Cheryl Druehl, Assistant Professor, George Mason University, 4400
University Dr, MS 5F4, Fairfax, VA, 22030, United States of America,
cdruehl@gmu.edu, Michael Naor
We investigate the impact of considering cost evolution due to learning by doing in
the selection of materials for a manufacturing firm. A multi-product, multi-period
selection framework is developed to analyze the problem because single-product
selection methods are unable account for benefits realized through shared learning
among products. The use of test beds as a strategy for introducing new materials to
a firm is also evaluated.
An innovative new business model for sustainable transportation is described. A
case study approach is used to study the unique product and service development
process required to electrify the automobile industry, focusing on a clean tech
company building innovative green infrastructure for sustainable transportation in
Israel.
403
WB56
■ WB56
3 - A Regime-switching Approach to the Valuation of Weather Options
M.I.M Wahab, Ryerson University, Toronto, ON, M5B 2K3, Canada,
wahab@ryerson.ca, R. S. Elias, L. Fang
C - Room 1, Level 1
Human Decision-Making and Social
Network Simulation
Regime-switching processes are used to model the stochastic behavior of
temperature with aim of valuation of temperature-based weather options. Three
different models are used to predict the expected heating degree days (HDD) and
cooling degree days (CDD) that play a crucial role in valuation of weather options.
Temperature dataset from Toronto, Canada, is used for the analysis. Results
demonstrate that one of the models captures temperature dynamics more accurately
than the other two models.
Sponsor: Simulation Society
Sponsored Session
Chair: Young-Jun Son, Professor, The University of Arizona, Systems and
Industrial Engineering, Tucson, AZ, 85721, United States of America,
son@sie.arizona.edu
1 - Hyper-Networks and Their Properties
W. K. Victor Chan, Assistant Professor, Rensselaer Polytechnic
Institute, ISE Dept, CII 5015, 110 8th Street, Troy, NY, 12180-3590,
United States of America, chanw@rpi.edu, Cheng Hsu
4 - Path-Vector Contracting: Profit Maximization and Risk Management
Praveen Kumar, Rensselaer Polytechnic Inst, 110 8th Street,
Troy, NY, United States of America, muthup@rpi.edu
We consider an Internet Service Provider’s problem of providing end-to-end (e2e)
services with bandwidth guarantees, using a path-vector based approach. The spotpricing framework for e2e bandwidth guaranteed services utilizes a path contracting
strategy by formulating it as a stochastic optimization problem with the objective of
maximizing expected profit subject to risk constraints.
A hyper-network is an integration of multi-layered (role-based) connections of
members in a community, such as the Internet and an ecosystem. In this talk, we
formally define hyper-networks and present their analytical properties. We show
that hyper-networks can reveal otherwise hidden social structures and provide
estimation formulae for determining average vertex-vertex distances and average
vertex degrees.
5 - Flash Crashes - Volatility, Smart Order Routing, and
Market Fragmentation
Bruce Weber, London Business School, Regent’s Park, London,
NW14SA, United Kingdom, bweber@london.edu
2 - Simulation-based Workforce Assignment Considering Position in a
Social Network
Nurcin Celik, PhD, The University of Arizona, 1127 E James E.
Rogers Way, Tucson, AZ, 85721-0020, United States of America,
nurcinkoyuncu@gmail.com, Dong Xu, Hui Xi, Young-Jun Son,
Robin Lemaire, Keith Provan
Advances in IT have lowered costs but also fostered trading practices that may
negatively impact the entire market. A national market system for securities with
multiple fragmented liquidity pools is simulated. We analyze how trading rules at
different exchanges and software for smart order routing can lead to illiquidity and
“flash crashes.” Under certain conditions, high frequency trading can lead to
securities market aberrations, and curbs on computer-driven trading may be
warranted.
A novel modeling framework is proposed to help managers devise optimal
workforce assignments that consider both short and long-term aspects of the
organizational social network. The framework involves the evaluation module (via
agent-based simulation) to calculate the position and equivalence values between
each pair of workforce members and the assignment module (via multi-objective
optimization) to select an optimal workforce mix. The framework is illustrated with
the Kuali organization.
■ WB58
C - Room 3, Level 1
Finance-Theory and Empirics
3 - Dynamic Control and Simulation of Manufacturing Process with
Different Forms of Uncertainties
Hyunsoo Lee, Texas A&M University, 3131 TAMUS, College Station,
TX, 77843, United States of America, hsl@neo.tamu.edu,
Amarnath Banerjee
Contributed Session
Chair: Vinod Cheriyan, Georgia Institute of Technology, Industrial and
Sytems Engineering, 765 Ferst Drive NW, Atlanta, Georgia,
vinod.cheriyan@gatech.edu
1 - The Empirical Research of Media Effect in China Stock Market
Yahui Zhang, The School of Management, Xi’an Jiaotong University,
#28 Xianning West Road, Mailbox 1875, Xi’an, China,
kailey@stu.xjtu.edu.cn, Leiming Fu, Difang Wan
We show a method for capturing and dynamically controlling uncertainties under
changes in manufacturing condition. Ambiguity and variance type uncertainties are
incorporated into a Fuzzy colored Petri Net with stochastic time delay model and it
is controlled using a new and effective learning method for simulation-based
optimization. A semiconductor process with serial and batch machines is controlled
and a given objective is achieved using the suggested simulation based optimization
method.
This research explores the existence of media effect in China stock market through
event research and analyses the affecting factors. Results show that media effect is
significant and presented as negative cumulative abnormal return within the event
window, which can be mitigated by better corporate governance. CAR is positively
correlated with the B/M ratio of equity, financial leverage, ROA and position
accumulation significantly, the affect of firm size and news type are not significant.
■ WB57
C - Room 2, Level 1
2 - MIDAS Instruments for Multiple Parameters
Stephen Goldberger, PhD candidate, UNC, University of North
Carolina, Chapel Hill, NC, 27514, United States of America,
sgoldber@email.unc.edu
Financial Optimization in Energy and
Communication Systems
Sponsor: Financial Services Section
Sponsored Session
Many Time Series models in Econometrics are dependent on the condition that an
error term is expected to be zero given all information available at the beginning of
time t. I extend the MIDAS (Mixed Data Sampling) Instruments framework
developed by Eric Ghysels and Johnathan Wright to create a GMM estimator for a
vector of parameters dependent on this moment condition.
Chair: Jim Bander, Credit Risk Optimization Manager,
Toyota Financial Services, 3200 W Ray Road, Chandler, AZ, 85226,
United States of America, jim.bander@gmail.com
1 - Energy Portfolio Investment with Entry Decisions
Zhen Liu, Assistant Professor, Missouri University of Science &
Technology, United States of America, zliu@mst.edu, Scott Grasman,
Jianjun Deng
3 - Can Oil Prices Help Estimate Commodity Futures Prices? The
Cases of Copper and Silver
Gonzalo Cortazar, P. Universidad Catolica de Chile, Vicuna
Mackenna 4860, Santiago, Chile, gcortaza@ing.puc.cl,
Francisco Eterovic
We formulate energy portfolio problems as an optimization problem to maximize
long-term profit through stochastic control and numerical analysis methods, and
solve the following problems: (1) the optimal time to build a new alternative green
energy power generating plant, and (2) the optimal dispatch from the existing coal
plant and the new plant.
We use prices of long term oil futures contracts to estimate copper and silver prices.
We show that the Cortazar et al (2008) multi-commodity model applied to oilcopper and oil-silver which have low correlation seems not to be effective. We then
propose a modified multi-commodity model that uses the non-stationary long term
process of oil to help estimate long term copper and silver futures prices, achieving a
much better fit than using available individual or multi-commodity models.
2 - Reducing Price Volatility of Electricity Consumption for a Firm’s
Energy Risk Management
Xiaohua Wu, Rensselaer Polytechnic Institute, 903 Peoples Ave
Apt 3, Troy, NY, 12180, United States of America, wux4@rpi.edu,
Aparna Gupta
Smart Grid technologies allow firms to manage electricity price volatility and
fluctuations. We develop a framework to assess strategies for optimally shifting peak
load consumption using distributed storage systems of Smart Grids. Risk
management is achieved by optimal investment in storage systems and peak load
shifting under stochastic electricity prices.
404
4 - A Bounded-rational Model of Price Bubbles and Business Cycles
Vinod Cheriyan, Georgia Institute of Technology, Industrial and
Sytems Engineering, 765 Ferst Drive NW, Atlanta, GA,
vinod.cheriyan@gatech.edu, Anton Kleywegt
3 - A Colored Stochastic Petri Net Based Approach to Performance
Analysis of JFK International Airport
Poornima Balakrishna, Sensis Corporation, 11111 Sunset Hills Rd,
Suite 130, Reston, VA, 20190, United States of America,
pbalakri@sensis.com
Various markets exhibit growth and collapse in prices that are sometimes called
bubbles. Related to that is the notion of business cycles. We consider a model in
which investors behave reasonably, although with imperfect expectations, that
attempt to provide insight into the formation of bubbles and business cycles. We
also present results on the convergence of the process to an attractor that describes
a business cycle, and consider where in the cycle most time is spent.
We model the airport departure process using colored stochastic Petri nets and
airport surveillance data. This formal specification of the probabilistic airport system
is then analyzed through simulation. The use of surveillance data in the model
enables identification of bottlenecks on the airport surface including gate area and
taxiway intersections. We measure congestion through analysis of queue lengths,
delays and resource utilization and report on both airline and airport performance.
4 - Estimation of Airport Performance Metrics
Ioannis Simaiakis, PhD Candidate, Massachusetts Institute of
Technology, 77 Massachusetts Avenue, Cambridge, MA, 02139,
United States of America, ioa_sim@mit.edu, Hamsa Balakrishnan
■ WB61
Operations Management VI
Operational throughput and taxi times are two key metrics of airport performance.
In this work, we show how the maximum throughput capacity of an airport can be
represented as a function of arrival and departure demand. We also illustrate how
unimpeded taxi times may be estimated by representing taxi time as a function of
takeoff and the queues. We use convex-optimization to estimate these metrics
without assuming the form of the solutions, and by only imposing operational
constraints.
Contributed Session
Chair: Andrew Kach, Doctoral Student, New Mexico State University,
Department of Management, P.O. Box 3001, Las Cruces, NM, 88003,
United States of America, akach@nmsu.edu
1 - Advance Demand Information, Capacity Restrictions and
Customer Prioritization
Bisheng Du, PhD Student, Aarhus University, Fuglesangs Alle 4,
Department of Business Studies, Aarhus, 8210, Denmark,
bisd@asb.dk, Christian Larsen, Alan Scheller-Wolf
■ WB63
We study a single supplier with fixed capacity selling products to buyers having
different priorities. The buyers can place pre-orders before their demand is observed,
and can also issue additional orders upon observing updating demand information.
Since the supplier guarantees delivery of pre-ordered goods (these are not
constrained by her capacity) buyers with lower priorities may consider pre-ordering
in order to secure inventory. We find optimal policies for the supplier and buyers.
Game Theory and Homeland Security
Sponsor: Decision Analysis
Sponsored Session
Chair: Jun Zhuang, Assistant Professor, University at Buffalo, SUNY, 403
jzhuang@buffalo.edu
1 - Mixed Strategy Nash Equilibria in Symmetric Signaling Games
Barry Cobb, Virginia Military Institute, 335 Scott Shipp Hall,
Lexington, United States of America, cobbbr@vmi.edu, Atin
Basuchoudhary, Gregory Hartman
2 - Centrality and Heterogeneity During the Evolution of
Inter-organisational Networks
Nuno Oliveira, PhD Student, LSE, Houghton Street, London,
United Kingdom, n.r.oliveira@lse.ac.uk
Although extant research has reported a linkage between network centrality and
heterogeneity, the understanding on the co-evolution of both variables is little. For a
inter-organisatitional network of a 48 million British pounds building project, we
show that network heterogeneity decreases whilst network centrality has a U-shape
throughout a 3-year period. Implications for researchers and practitioners are also
presented.
Signaling games are characterized by asymmetric information where the more
informed player has a choice about what information to provide to its opponent.
Decision trees are used to derive the Nash equilibrium strategies for signaling games
where the more informed player has an arbitrary number of possible types. The
technique is demonstrated by analyzing an interactive game between a terrorist and
a governmental agency.
3 - Security as a Moderator of Stress on Airline Performance
Andrew Kach, Doctoral Student, New Mexico State University,
Department of Management, P.O. Box 3001, Las Cruces, NM, 88003,
United States of America, akach@nmsu.edu, Jeffrey Teich
2 - Solving Massive Scale Security Games with Arbitrary Schedules:
A Branch and Price Approach
Milind Tambe, University of Southern California, 3737 Watt Way,
PHE 410, Los Angeles, CA, 90089, United States of America,
tambe@usc.edu, Manish Jain, Fernando Ordonez, Chris Kiekintveld,
Erim Kardes
Heightened security in airports is used as a preventative action to reduce passenger
engagement in terrorist acts or disruptive behavior; however, high safety measures
may have an adverse impact on airline performance. More specifically: How does
increasing levels of security impact the relationship between passenger stress levels
on airline performance?
Security games are used in deployed decision-support tools in use by LAX police
and the Federal Air Marshals Service. The algorithms used to solve these games find
optimal randomized schedules to allocate security resources for infrastructure
protection. Unfortunately, the state of the art algorithms fail to scale to large
problems with arbitrary scheduling constraints. We introduce ASPEN, a branch-andprice approach that overcomes this limitation.
■ WB62
Aviation Applications IV
3 - Quantifying Unobserved Attributes in Expert Elicitation of
Terrorist Preferences
Chen Wang, University of Wisconsin-Madison, 3237 Mechanical
Engineering, 1513 University Avenue, Madison, WI, 53706,
United States of America, cwang37@wisc.edu, Vicki Bier
Contributed Session
Chair: Ioannis Simaiakis, PhD Candidate, Massachusetts Institute of
Technology, 77 Massachusetts Avenue, Cambridge, MA, 02139, United
States of America, ioa_sim@mit.edu
1 - Future Aircraft Network and Schedules
Yan Shu, Graduate Student, Georgia Institute of Technology, 686
Cherry Street, Atlanta, 30332, United States of America,
yshu@gatech.edu, Ellis Johnson, Barry Smith, John-Paul Clarke
A terrorist values targets according to a multi-attribute utility function in which
some attributes are unknown to the defender. A group of experts ranks potential
targets by their attractiveness to the terrorist. The defender infers the weights of the
known attributes, and the importance of the unobserved attributes, using either
probabilistic inversion or Bayesian density estimation.
We propose a three-step approach to build flight schedule from scratch. We
implement our algorithms into solutions.
4 - Modeling Arbitrary Layers of Continuous Level Defenses in Facing
with A Strategic Attacker
Jun Zhuang, Assistant Professor, University at Buffalo, SUNY, 403
jzhuang@buffalo.edu, Mohsen Golalikhani
2 - Optimizing Staffing Plans at Airports
Prem Kumar Viswanathan, Scientist, Transport and Mobility
Laboratory, Ecole Polytechnique Federale de Lausanne, GC B3 435,
EPFL, Ecublens, VD, 1015, Switzerland, prem.viswanathan@epfl.ch,
Michel Bierlaire
Minimizing operating costs for maintaining ground personnel at airports is a
complex problem due to uneven flight activities, passenger service expectations and
staffing inflexibilities due to shift durations. In this work, we develop a method to
find optimal shift timings that considers non-productive time due to activity
changeovers, the mix of full-time and part-time workers and passenger waiting time
criteria.
WB63
We propose a class of models for the optimal assignment of defensive resources in a
game between a defender and an attacker. The novelty of our model is that we
allow the defender to assign her continuous-level defensive resources to any subset
(or arbitrary layers) of targets due to functional similarity or geographical proximity.
The results show that our model could significantly increase the defender’s payoff,
especially when the cost of defense is high, or the attack cost is intermediate.
405
WB64
■ WB64
■ WB65
Health Care, Modeling and Optimization VI
Inventory Management VII
Contributed Session
Contributed Session
Chair: Song Chew, Assistant Professor, Southern Illinois University
Edwardsville, Edwardsville, Edwardsville, IL, 62026, United States of
America, schew@siue.edu
1 - Simulating Clinics: The Challenge of Data Collection and Analysis
Helida Dodd, President, Dodd Consulting Group, 10223 SW 89 St,
Miami, FL, 33176, United States of America, helida@doddcg.com,
Martha Centeno
Chair: Haitao Li, University of Missouri - St. Louis, 229 CCB, One
lihait@umsl.edu
1 - Making Better Fulfillment Allocation Decisions on the Fly
Jason Acimovic, Massachusetts Institute of Technology,
77 Massachusetts Ave, E62-459, Cambridge, MA, 02139,
United States of America, acimovic@mit.edu, Stephen Graves
We discuss a simulation study of an Endoscopy center, challenges, and lessons
learned. The goal of the project was to find ways to increase throughput to 80
patients/day. It was quickly apparent that the stumbling block would be the lack of
data available. Some data is collected via the information system, but there is no
reporting application to measure performance. Data is also collected manually
sporadically in different areas, but it is not readily analyzed because of the lack of
manpower.
E tailers manage complicated distribution networks, serving customers with
heterogeneous service time requirements. What is the best way to fulfill each of
these customers’ orders for items with low inventory levels? We partner with an etailer to examine this question. We find the value of the improvement gap by
comparing a greedy strategy with an ex post facto optimization. We then develop an
approximate dynamic programming heuristic and evaluate its performance on toy
and actual examples.
2 - Simulation-based Optimal Staffing Policies Under Cyclic Demand
Mina Loghavi, University of Tennessee, 331 SMC, 916 Volunteer
Blvd., Knoxville, TN, 37996, United States of America,
mloghavi@utk.edu, Robin Clark, Charles Noon, Bogdan Bichescu
2 - Two-stage, Two-product, Capacitated Supplier Problem with
Uncertain Demand
Ramesh Bollapragada, Associate Professor, College of Business, San
Francisco State University, 1600 Holloway Avenue, San Francisco,
CA, 94132, United States of America, rameshb@sfsu.edu, Laoucine
Kerbache, Kai Luo
We consider the objectives of minimizing staffing cost and maintaining acceptable
patient waiting times in an emergency department (ED). We employ simulation and
optimization to explore the best policies for ED staffing over repeating cycles of
stochastic demand. In contrast to SIPP-based methods, this approach is feasible in
periods when demand temporarily exceeds capacity and when additional constraints
are present. We present insights from computational analysis on real-world datasets.
We investigate a finite-horizon two-product (expensive and cheaper product from
capacitated local and far-away suppliers, respectively), one retailer problem with
two-stages, and uncertain demand. In the first stage, we determine the order
quantity vector to place with suppliers, and in the second stage we determine the
allocation of inventory to the two products given limited shelf-space. Optimal and
heuristic solutions are discussed.
3 - Setting Staffing Levels Under Time-varying Demand in the Context
of an Emergency Department
Mieke Defraeye, PhD Student, K.U.Leuven, Naamsestraat 69,
Leuven, Belgium, mieke.defraeye@econ.kuleuven.be,
Inneke Van Nieuwenhuyse
3 - Optimal Control of a Manufacturing/Remanuacturing Systems with
Quality Grade Differentiation
Morteza Pourakbar, Erasmus University Rotterdam, BurgOudlaan 50,
Rotterdam, Netherlands, pourakbar@few.eur.nl, Mohsen Elhafsi,
Saif Benjaafar
When determining capacity levels in a healthcare system (such as an emergency
department), a key feature that has to be taken into account is the time-varying
demand for service. Due to these fluctuations in demand, determining capacity
levels to achieve a certain service level is often complicated. In this presentation, an
approach to determine staffing levels that results sufficiently small waiting times,
will be presented.
We consider a manufacturing/remanufacturing system where each demand is
coupled with the return of an item that may be remanufacturable. Returned items
differ in their quality grades with grades affecting remanufacturing cost and time.
Decisions must be made regarding whether or not to accept a returned item and
whether to produce a new item or remanufacture a returned one and if so from
which grade.
4 - Applying Inventory Control Practices Within the Sisters of Mercy
Health Care Supply Chain
Server Apras, University of Arkansas, 1343,N.Leverett,15,
Fayetteville, AR, 72703, United States of America, sapras@uark.edu
4 - New Model and Heuristics for Safety Stock Placement in General
Acyclic Supply Chain Networks
Haitao Li, University of Missouri - St. Louis, 229 CCB,
One University Blvd, St. Louis, MO, 63121,
United States of America, lihait@umsl.edu, Dali Jiang
The goal of this research is to lay a foundation for the application and acceptance of
more advanced inventory control practices within the healthcare supply chain.The
project examines the demand characteristics and optimal control policies for bulk
pharmaceuticals within the Sisters of Mercy’s network to compare to the current
ordering and inventory control strategies to document potential cost savings.Also,a
multiechelon inventory analysis examines the benefits of centralized inventory
control
We model the safety stock placement problem in general acyclic supply chain
networks as a project scheduling problem, for which the constraint programming
(CP) techniques are both effective and efficient in finding high quality solutions. We
further integrate CP with a genetic algorithm (GA), which improves the CP solution
quality significantly. The performance of our hybrid CP-GA algorithm is evaluated
on randomly generated test instances. CP-GA is able to find optimal solutions to
small problems in fractions of a second, and near optimal solutions of about 5%
optimality gap to medium size problems in less than two minutes on average.
5 - Outpatient Appointment Scheduling using Genetic Algorithms
Song Chew, Assistant Professor, Southern Illinois University
Edwardsville, Edwardsville, Edwardsville, IL, 62026,
United States of America, schew@siue.edu
Outpatient appointment scheduling has been an active area of research. The goal of
the research is to strike a balance between patient waiting time, and doctor idle time
and overtime. The objective of our work is to determine the optimal total number of
patients for a clinical session, and the optimal number of patients assigned to each
time slot in the session so as to minimize the total cost using genetic algorithms.
■ WB66
Facilities Planning and Design
Contributed Session
Chair: Li Zhang, Royal Bank of Scotland, 399 Main Ave., Apt 614,
Norwalk, CT, 06851, United States of America, lieezhang@gmail.com
1 - Framework for Measuring Rationale Clarity of Collaborative
Design Decisions
States of America, john.m.chachere@nasa.gov, John Haymaker
Designers often must convey clear rationale supporting design decisions. We define
rationale as a set of assertions about components (managers, stakeholders,
designers, gatekeepers, goals, constraints, alternatives, and analysis) with variable
clarity (coherent, concrete, connected, consistent, credible, certain, and correct). We
relate these definitions in the Rationale Clarity Framework to enhance objectivity in
evaluating tools and processes for design decision making.
406
2 - Order and Inventory Management System for a Food Bank
Arsalan Paleshi, PhD Student, University of Louisville, Department
of Industrial Engineering, JB Speed School of Engineering,
Louisville, KY, 40292, United States of America,
a0pale01@louisville.edu, Bulent Erenay, Trivikram Rao
WB69
Based on simulations by Dr. Paul Jensen and W.G. Lesso, “Advanced PNG Game” is
a single product simulation using spreadsheets. The standard deviation of demand,
lead time, and production level can be adjusted, for a cost, in each of the 52
simulated weeks. The objective is to minimize total cost.
4 - Agent-based Simulation for Emergency Evacuation of
Heterogeneous Populations in a High-rise Building
Jeongin Koo, PhD Student, POSTECH, San31, Hyoja-Dong, Namgu,
Pohang, Korea, Republic of, xession@postech.ac.kr, Yong Seog Kim,
Byung-In Kim
This project creates an Excel tool to support a food bank’s need for a less labor
intensive, inexpensive ordering and inventory management system. Additionally
application of lean principles like KANBAN, ANDON and visual management to
control inventory are suggested. The extension of similar methods for other cases is
also discussed.
An efficient evacuation plan is critical for the safety of residents in high-rise
buildings during catastrophic events. Although there are some research works on
building evacuation using simulation, most of them do not consider the
handicapped people. This research presents an agent-based simulation of
heterogeneous populations including various types of people with disabilities for a
24-story real world building evacuation. Using the model, several evacuation plans
are tested and evaluated.
3 - A Study of Spine Layout for Semiconductor Manufacturing Plant
Under the Multi-Floor Environment
Chikong Huang, Professor, National Yunlin University of Science &
Technology, 123 University Rd., Sec. 3, Department of Industrial
Management, Touliu, Yunlin, 640, Taiwan - ROC,
huangck@yuntech.edu.tw, Ming-Ru Tsai
This study focuses on the spine layout in multiple floors by arranging workstations
along several closed-loop moving tracks. The objective is to minimize the horizontal
and vertical handling costs. The model and solution algorithm using Tabu search are
developed and they are also verified by a numerical example.
■ WB68
4 - Layout Analysis and Lead-time Calculations with PEM Forklifts
Abhijit Gosavi, Missouri University of Science and Technology, 219
Engineering Management, Rolla, MO, 65409, United States of
America, gosavia@mst.edu, Suzanna Long, Scott Grasman
Innovation/Entrepreneurship II
Contributed Session
Chair: David Gomulya, Foster Business School, University of Washington,
MacKenzie 355, Box 353200, Seattle, WA, 98195,
United States of America, dgomulya@u.washington.edu
1 - Institutional Conditions and Venture Capital Investment in
Developing Countries
Theodore Khoury, Oregon State University, Bexell 422B, Corvallis,
OR, 97331, United States of America,
ted.khoury@bus.oregonstate.edu, Marc Junkunc, Santiago Mingo
PEM forklifts utilize hydrogen-based fuels and have been shown, in certain
conditions, to be more economical than traditional battery-powered forklifts. We
analyze the impact of using PEM forklifts on manufacturing layout and the lead
time, including material-handling time, calculations. We use simulation to compare
layouts that use PEM forklifts and battery-powered forklifts on the basis of the lead
time and the empty travel time.
5 - Kernel Method of Performance Estimation in Autonomous Vehicle
Storage and Retrieval Systems
Li Zhang, Royal Bank of Scotland, 399 Main Ave., Apt 614, Norwalk,
CT, 06851, United States of America, lieezhang@gmail.com,
Changjian Huang
Focusing on entrepreneurial ventures in developing countries, we explore how
venture capital (VC) investments are shaped by firms’ stage of development and
host country institutional conditions. Using a panel of 443 VC investments occurring
in Latin America over 12 years, we find that larger investments are affiliated with
later stage firms, higher transaction costs and lower political hazard risk. Also,
political hazards moderate the relationship between development stage and
investment size.
In this study, a systematic simulation combined with kernel learning method is
proposed for use in Autonomous Vehicle Storage and Retrieval Systems (AVS/RSs).
The proposed method reflects the nonlinear relationship between system
performance and factors and provides universal usage in performance estimation for
various system designs. Simulation results indicate that the developed models
provide accurate and computational efficient estimations.
2 - New Ventures and Timing of Alliance Formation: The Dynamics of
Temporal Congruence and Contingency
David Gomulya, Foster Business School, University of Washington,
MacKenzie 355, Box 353200, Seattle, WA, 98195, United States of
America, dgomulya@u.washington.edu
■ WB67
While alliances have been shown to increase new-venture survival, the literature
remains silent regarding the effect of timing of alliance formations. Related
literatures regarding timing have also been unable to explain their conflicting
findings, which show the effect of timing can range from positive to negative. To fill
gaps, I develop a novel model based on temporal changes during pre- and postformation phases of an alliance. I show the effect can indeed range from positive to
negative.
Simulation II
Contributed Session
Chair: Byung-In Kim, Associate Professor, Pohang University of Science
and Technology, Nam-Gu, Hyoja-Dong, POSTECH, Pohang, Korea,
Republic of, bkim@postech.ac.kr
1 - Revenue Management Under Customer Choice Behavior
Marco Bijvank, University of Montreal, CP 6128 Succ Centre-Ville,
Pavillon André-Aisenstadt, Montreal, QC, H3C 3J7, Canada,
bijvankm@iro.umontreal.ca, Pierre L’Ecuyer
■ WB69
Joint Session TSL/ SPPSN: Risk and Recovery of
Transportation Networks to Disaster
Observations from practice and recent research suggest a shift to customer oriented
revenue management. During this presentation we discuss how to design a
simulation tool to incorporate very general demand processes and different discrete
choice models. We also show how this tool can be applied in practice to understand
the customer choice decision making.
Sponsored Session
2 - Formation Control Strategies for Groups of Mobile
Autonomous Agents
Wei Zhao, IBM Research - China, Diamond Building,ZGC Software
Park, Beijing, China, wzhaow@cn.ibm.com, Wenjun Yin, Jin Dong,
Bin Zhang, Ming Xie, Long Wang
Chair: Nicholas Lownes, Assistant Professor, University of Connecticut,
261 Glenbrook Rd., U-2037, Storrs, CT, 06269, United States of America,
nlownes@engr.uconn.edu
1 - Resilience of Fright Transportation Networks
Xiaodong Zhang, University of Maryland, College Park, MD, 20742,
United States of America, xzhang@umd.edu, Elise Miller-Hooks,
Reza Faturechi
This paper presents the control strategies for multiple mobile autonomous agents to
achieve leader-following formations. Each follower agent establishes a Bezier
trajectory between its current position and that of its leader agent. Considering the
nonholonomic properties of the agent, the optimization of Bezier curve’s curvature
to choose appropriate scale factor is conducted by penalty function method.
Simulations and experimental results show the effectiveness of our control
strategies.
The problem of measuring network resilience in transportation networks and
determining optimal pre-event remedial actions is formulated as a two-stage
stochastic program. The formulation explicitly recognizes that post-disaster
performance depends not only on the inherent capability of the system to absorb
externally induced changes, but also on the actions that can be taken in the
immediate aftermath of the disaster to restore system performance. An L-shaped
method is proposed for its solution.
3 - Demonstrating Simulations of Inventory and Production
Management using VBA in Microsoft Excel
Amanda Baty, Texas Tech University, 3424 Frankford Ave
Apt 8B, Lubbock, TX, 79407, United States of America,
amanda.baty@ttu.edu, Dr. Rafael Moras
407
WB70
2 - Debris Operations
Kael Stilp, Georgia Institute of Technology, 765 Ferst Drive, NW,
Atlanta, GA, United States of America, mstilp3@isye.gatech.edu,
Monica Villarreal, Antonio Carbajal, Ozlem Ergun, Pinar Keskinocak
The paper is drawn from an analysis by DEA of patient referral costs on behalf of a
Primary Care Trust (PCT) in England. The paper focuses on General Practitioners
(GPs) contracted to the PCT. GPs are the gateway to health services in England.
Clinical decisions by GPs heavily influence referral costs incurred by the PCT. The
paper formulates models to determine the scope for savings in referrals costs and
decomposes them into those attributable to mix of in and out patient referrals and
those attributable to price differentials between in and out patient cases.
Debris operations following a disaster is a lengthy and costly process, involving
multiple interrelated stages. Each stage contains a unique set of social fairness
concerns with which need to be considered as well the computationally difficult
objectives of efficiency. We present an encompassing set of models with
computational analysis of each stage and discuss their interrelated nature.
2 - A Decade of Clinical Productivity Change and the Determinants of
Relative Clinical Efficiency in Pennsylvania Coronary Artery Bypass
Graft Programs
Jon Chilingerian, Brandeis University, The Heller School for Social
Policy and Management, South Street, Waltham, MA, 02454-9110,
United States of America, chilinge@brandeis.edu
3 - Many-to-many Transportation Network Risk Assessment
Qixing Wang, University of Connecticut, 261 Glenbrook Road, Unit
2037, Storrs, CT, 06269, United States of America,
qiw09005@engr.uconn.edu, Nicholas Lownes
We present evidence on the growth of clinical productivity change in hospitals
performing coronary artery bypass grafts (CABGs) over a decade. Analyzing
outcome and severity-adjusted hospital clinical in Pennsylvania between 1994-2004,
frontier methodology was used to measure and evaluate clinical productivity
change, medical progress (i.e., shifts in the clinical frontiers), and relative clinical
efficiency over time. In Pennsylvania, the average hospital’s clinical productivity for
CABG surgeries grew by more than 30%. We found strong support, however, that
medical-technical progress, rather than improvement in clinical efficiency, was the
underlying reason for the growth. Factors associated with clinical efficiency
included: employing hospitalists; having a higher percent of salaried physicians in
relation to FTEs on salary; and strategic choices that focused on open heart
cardiovascular surgeries. All of these factors are associated with performance and
are under a clinical department’s control.
This work presents an extension to game-theoretic network risk models through the
many-to-many application. A model that can be applied to large-scale networks is
presented along with application results. Results provide a measure of link risk and
can be used as decision support for sensor placement strategies.
■ WB70
Emerging Applications in Aviation
3 - DEA in the 100 Largest U.S. Public School Districts
N.K. Kwak, Saint Louis University, Department of Decision Sciences
and MIS, St. Louis, MI, United States of America, kwakn@slu.edu,
Walter Garrett
Sponsored Session
Chair: Wenwei Cao, Doctoral Student, Georgia Institute of Technology,
765 Ferst Dr NW, GA-Tech ISyE, Atlanta, GA, 30332-0205, United States
of America, cww@gatech.edu
1 - The Role of Air Travel in the Worldwide Spread of Vector
Borne Diseases
Lauren Gardner, Graduate Research Assistant, University of Texas at
Austin, Earnest Cockrell Jr. Hall, 6.204, Austin, TX, 78712, United
States of America, lmgardner@mail.utexas.edu, David Fajardo,
Travis Waller
This paper reports on a study of the 100 largest U.S. public school districts, which
are together responsible for educating 22 percent of all public school students. Using
data from the U.S. Department of Education, we use DEA to assess the efficiencies
of those districts and to identify common characteristics of efficient districts. The
results may be useful for benchmarking inefficient districts to improve their
performance.
■ WB72
Increased passenger air traffic has lead to an increased risk of importation and
establishment of vector-borne diseases. As such, it is critical to be able to identify the
risk associated with air travel routes between vector-compatible environments. This
problem requires modeling the interaction between three overlapping networks: a
vector survivability network, a social network and an airport network. We study the
the role of the airport network in connecting the vector-survivability network.
Facility Logistics III
Sponsored Session
2 - Crew Rostering in Fractional Airlines
Wenwei Cao, Doctoral Student, Georgia Institute of Technology, 765
Ferst Dr NW, GA-Tech ISyE, Atlanta, GA, 30332-0205, United States
of America, cww@gatech.edu, Ellis Johnson, Ozlem Ergun
Chair: Ananth Krishnamurthy, University of Wisconsin, 1513 University
Ave, Madison, United States of America, ananth@engr.wisc.edu
1 - Modeling Inventory Visibility in Supply Chain Networks
Sandeep Srivathsan, Research Associate, Oklahoma State University,
School of IE&M, 322 EN, Stillwater, OK, 74078, United States of
America, sandeep.srivathsan@okstate.edu, Manjunath Kamath
We consider a crew rostering problem in fractional airlines where rosters are
generated through a bidding process. Instead of creating bid-lines beforehand, the
management can only control the capacities on schedule lines and vacation periods.
We propose an optimization based framework for capacity decision-making. Within
the framework, a model incorporating training considerations is solved via column
generation.
We develop stochastic models of two-echelon supply chains where a retailer has
visibility of production facilities’ net inventory levels and vice versa. Order
placement and fulfillment policies depend on the net inventory levels and the
models developed can be used to obtain insights into the benefits of inventory
visibility on overall supply chain performance. We present models developed under
Markovian assumptions and then discuss strategies to develop models for more
general settings.
3 - Transforming US Army Supply Chains: An Analytical Architecture for
Enterprise Management
Greg Parlier, Institute for Defense Analyses, Madison, AL,
United States of America, gparlier@ida.org
2 - Evaluation of Decision Criteria to Select Efficient Order
Picking Systems
Detlef Spee, Detlef.Spee@iml.fraunhofer.de, Tim Geissen,
Michael ten Hompel
A comprehensive analytical architecture to enable US Army Logistics
Transformation is presented, incorporating an “engine for innovation” to accelerate
and sustain continual improvement. Strategic management challenges are
addressed, including decision support systems, human capital investment needs,
organizational design and strategic alignment for a learning organization.
Order picking systems contribute to the competitive capability of companies.
Increased requirements regarding performance and quality aspects necessitate
flexible systems that meet present and future demands. The paper focuses on the
decisions which are made during the planning process to select a proper order
picking method. Therefore, relevant order picking methods are systematized and
selection criteria are evaluated by the use of a market study amongst suppliers of
order picking systems.
■ WB71
Health and Education Applications of DEA
3 - Estimating the WIP on a Conveyor Based Material Handling System
with Multiple Stations
Dima Nazzal, Assistant Professor, University of Central Florida, 4000
Central Florida Blvd., Orlando, FL, 32816, United States of America,
dnazzal@mail.ucf.edu, Vernet Lasrado
Invited Session
Chair: Emmanuel Thanassoulis, Aston University, Operations &
Information Management Group, Birmingham, AL,
United States of America, e.thanassoulis@btinternet.com
1 - Analysis by DEA of Health Referral Costs in England
Emmanuel Thanassoulis, Aston University, Operations & Information
Management Group, Birmingham, AL, United States of America,
e.thanassoulis@btinternet.com, Maria C. Portela, Mike Graveney
We present a method to improve the estimates of the work in process (WIP) on a
closed loop conveyor. We estimate the total traveling WIP and the WIP waiting to
be loaded on the conveyor. A probabilistic distribution has been derived for the
loading process and we test this model with a detailed simulation of a
semiconductor manufacturing facility.
408
■ WB73
WC01
3 - The Design of Single-Line Demand Adaptive Systems:
An Evaluative Framework
Fausto Errico, CIRRELT, 2920, Chemin de la tour, Montreal, QC, H3T
1J4, Canada, Fausto.Errico@cirrelt.ca, Teodor Gabriel Crainic,
Federico Malucelli, Maddalena Nonato
Reducing Transportation Emissions and GHG
Sponsored Session
Demand-Adaptive Systems (DASs) display features of both traditional fixed-line bus
services and purely on-demand systems such as dial-a-ride. A DAS bus line serves a
given set of compulsory stops according to a predefined schedule. On the other
hand, passengers may issue requests for transportation between two optional stops,
inducing detours in the vehicle routes. The design of a DAS line is a complex
planning process. We propose, evaluate and compare several possible design
strategies.
Chair: Hakob Avetisyan, PhD Student, University of Maryland, College
Park, MD, United States of America, havetisy@umd.edu
1 - Freeway Congestion Mitigation and the Emissions
Minimization Problem
Alex Bigazzi, Portland State University, Portland, OR,
United States of America, bigazzi@pdx.edu, Miguel Figliozzi
We present a freeway control problem that not only minimizes delays but also takes
emissions into account. We formulate several variants of a freeway traffic control
problem. Utilizing real-world sensor data from Portland Oregon and calibrated
emissions models we present and analyze solution results under different traffic
conditions and levels of elasticity.
Wednesday, 1:30pm - 3:00pm
■ WC01
2 - Modeling a Novel Method for Reducing Transportation Greenhouse
Gas Emissions
Erica Wygonik, University of Washington, Seattle, WA,
United States of America, ewygonik@uw.edu, Anne Goodchild
Technology Policy and Energy Markets
Sponsored Session
A model is developed to evaluate parameters effecting emissions to consider the
environmental impacts of aggregating personal travel into shared-use services. This
model indicates whether shared-use vehicles show significant benefit to the
environment over personal vehicles, and under what conditions those emissions
savings would be realized, using grocery store shopping in Seattle, Washington as
the first case study to quantify and compare the total environmental impacts.
Chair: Ekundayo Shittu, Assistant Professor, Tulane University, 7
McAlister Dr., New Orleans, LA, 70118, United States of America,
eshittu@tulane.edu
1 - Volatility Pricing for Renewable Energy Sources
Xiaoyue Jiang, Assistant Professor, Tulane University,
7 McAlister Dr, New Orleans, LA, 70118, United States of America,
xjiang@tulane.edu, Geoffrey Parker, Ekundayo Shittu, Anjali
Sheffrin
3 - Greener Construction of Transportation Construction Projects
Through Optimization
Hakob Avetisyan, PhD Student, University of Maryland, College
Park, MD, United States of America, havetisy@umd.edu,
Elise Miller-Hooks, Suvish Melanta
In recognizing the negative effects of volatility to reliability of the power grid, we
have proposed an analytical framework that models capacity volatility by
capacity@risk and prices volatility through a QoS-centric capacity market
mechanism. In this work, we will apply this framework to renewable sources
including solar and wind. We will price each type of sources based on their volatility
characteristics. Real data from one of the ISOs in the US will be used to gain
practical insights.
Optimization-based techniques are presented that permit a contractor to develop an
equipment-usage plan that adheres to current environmental standards and
anticipated new regulations, accounting for recent laws that might affect
construction, and possible future carbon tax or cap and trade programs. These
techniques aid contractors in trading off project cost, duration and resulting GHG
emissions in bid development and aid contractors in making green construction
decisions.
2 - Flexible the Better? On the Design of RPS in Presence of Green
Consumers and Emissions Trading
Yihsu Chen, Assistant Professor, University of California Merced,
Merced, CA, 95343, United States of America,
yihsu.chen@ucmerced.edu, Lizhi Wang
■ WB74
Emissions trading, green pricing programs and renewable portfolio standard (RPS)
are three concurrent policies implemented in US to reduce reliance on fossil fuel
and GHG emissions. Despite their differences in policy targets, they are closely
related and integrated with competitive electric markets. We examines market
outcomes of two aspects of RPS design in this talk: bundling and double counting.
Public Transit IV
Sponsored Session
Chair: Luca Quadrifoglio, Assistant Professor, Texas A&M Univeristy,
CE/TTI bldg - Room 301I, 405 Spence St., College Station, TX, 77843,
United States of America, lquadrifoglio@civil.tamu.edu
1 - A Logit-based Assignment on a Transit Schedule Hypergraph
Mark Hickman, Associate Professor, University of Arizona, Civil
Engineering, 1209 E. Second St., Bldg 72, Tucson, AZ, 85721-0072,
United States of America, mhickman@email.arizona.edu,
Hyunsoo Noh
3 - The Influence of Market Structure and Policy on Technology
Portfolio Investments
Ekundayo Shittu, Assistant Professor, Tulane University,
7 McAlister Dr., New Orleans, LA, 70118, United States of America,
eshittu@tulane.edu, Geoffrey Parker, Xiaoyue Jiang
We study firms’ incentives to invest in a portfolio of technologies under different
markets and environmental policies. The impacts of policies are critical to
understanding how competition and energy production mix. We pay attention to
the representation of the technologies in the portfolio because of implications on
cost. We demonstrate intriguing results that describe how investments and adoption
incentives are shaped by strategic interactions between market structure and
regulatory policy.
A hyperpath has been a common network structure in transit assignment. Using the
hyperpath, we propose a logit-based transit assignment on a transit scheduled
network. We introduce a link-based and time-expanded network and two
hyperpath algorithms, and we investigate the stochastic user equilibrium situation
under hard capacity constraints.
2 - Evaluating the Use of “Transfers” for Improving Zoning
Paratransit Systems
Chung-Wei Shen, Texas A&M University, CE/TTI Building, Room
309C, 3136 TAMU, College Station, TX, 77840, United States of
America, tzungwei0610@yahoo.com.tw, Luca Quadrifoglio
For paratransit agencies, the zoning strategy divides their service area into smaller
zones to different provider to simplify the management. After dropping customers
off for cross zone trips, the vehicles will return without passengers on-board
resulting in deadheading miles. Using transfers on boundaries is a promising method
to decrease deadheading miles while applying zoning strategies. This study evaluates
the performance of transfers on zoning paratransit systems through simulation
method.
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WC02
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3 - A Study on Setting Recycling Subsidy for Waste PCs in Taiwan
Through Bi-level Nonlinear Programming
Hsu-Shih Shih, Professor, Tamkang University, Taiwan, ROC,
151 Ying-Chuan Rd., Tamsui, Taipei, 25137, Taiwan - ROC,
hshih@mail.tku.edu.tw, Chia-Wei Hsu, Bo-Han Huang
Energy I
Contributed Session
The study investigates a recycling subsidy decision for waste PCs in Taiwan through
bi-level nonlinear programming (BLNP) for environmental protection. The upperlevel unit is RFMB (Recycling Fund Management Board) which hopes to balance
the recycling fund and others by controlling the subsidy et al.; the lower-level’s is
the recycling industry which likes to get maximum profits by controlling the
recycling rate. The BLNP model can help obtain an optimal solution for the
recycling system.
Chair: Le Xie, Assistant Professor, Texas A&M University, 3128 TAMU,
216M Zachry Bldg, College Station, TX, 77843, United States of America,
lxie@mail.ece.tamu.edu
1 - Why Your Plug-in Vehicle with a 40-mile Battery Pack May
Only Go 25
Orkun Karabasoglu, PhD Candidate, Carnegie Mellon University,
5000 forbes ave. 402 Scaife hall, Pittsburgh, PA, 15213,
United States of America, karabasoglu@cmu.edu, Jeremy Michalek
4 - Design of Solar Radiation Management by Projecting Man-made
Particles to Counter Global Warming
Ka Shek Lee, Associate Professor, Department of Industrial
Engineering and Logistics Managemen, The Hong Kong University of
Science and Technology, IELM, HKUST, Kowloon, Hong Kong - PRC,
nlee@ust.hk, Bin Dai
We investigate the effects of driving patterns on the range, gasoline consumption,
greenhouse gas emissions, and lifecycle costs of conventional, hybrid, and plug-in
hybrid vehicles. We find that drive cycle (style) can have a greater effect on
consumption, cost and emissions than vehicle design or charging frequency. Plug-in
vehicle range drops 35% under aggressive, rather than standard cycles, and drive
cycle can affect which vehicles are optimal.
Currently, mitigation efforts to counter global warming such as carbon emission
reduction are proving time inefficient, therefore it desires for an alternative to cool
the earth on an emergency basis. In this study, we proposed to project atmospheric
man-made particles to manage the solar radiation. Fluid dynamics and scattering
theory are employed to model particles’ life time and radiation forcing to determine
particles’ size, projection height and amount required for selecting materials.
2 - Stochastic Control for Smart Grid Users with Flexible Demand
Yong Liang, PhD Student, University of California-Berkeley, 1117
Etcheverry Hall, Berkeley, CA, 94720, United States of America,
yongliang@berkeley.edu, Z. Max Shen, Alan Sanstad
5 - Performance Analysis on Introducing Intercity High-speed
Railway System
Bin Dai, HKUST, A601, HKUST, Kowloon, Hong Kong - PRC,
dbbudstar@gmail.com, Ka Shek Lee
We propose a stochastic optimal control model for smart grid users to make the
optimal energy usage decisions incorporating energy consumption and generation.
The main feature of this model is its ability to dynamically adjust consumptions by
responding to the pricing signals from the electricity grid, deal with stochastic new
job arrivals as well as scheduling the jobs based on their own deadlines. The model
leads to a dynamic programming problem, which is solved using ADP techniques.
Carbon emission reduction contributes to mitigate global warming. Transportation
accounts for 20% global carbon emission and electricity-powered railway system is
carbon efficient. In this study, discrete choice model is employed to capture the
travel demand shift by introducing high-speed railway system. Performance analysis
is conducted to evaluate the carbon emission reduction, energy and time saving
conditioning on intercity distance and city size. Results show its attractiveness.
3 - Quantifying the Economic Impact of Variable Energy Forecast on
Power System Scheduling
Le Xie, Assistant Professor, Texas A&M University, 3128 TAMU,
216M Zachry Bldg, College Station, TX, 77843, United States of
America, lxie@mail.ece.tamu.edu, Haifeng Wang, Jin Dong,
Wenjun Yin
■ WC04
The integration of variable resources such as wind and photovoltaic has posed
fundamental challenges to the operation of electric energy systems. We attempt to
quantify the value of variable energy forecast in improving the efficiency of power
system scheduling. We demonstrate in a realistic system that only by explicitly
valuing near-term prediction and inter-temporal variations in the system scheduling
model could the economic potential of these variable resources be fully utilized.
Sustainability I
Contributed Session
Chair: Thomas Sloan, University of Massachusetts Lowell,
1 University Avenue, College of Management, Lowell, MA, 01854,
United States of America, Thomas_Sloan@uml.edu
1 - Managing Pollution in Oligopolistic Markets with
Sustainability Constraints
Sung Hoon Chung, The Pennsylvania State University, 244 Leonhard
Bldg., University Park, United States of America, sxc447@psu.edu,
Robert Weaver
■ WC03
Environmental Operations
Contributed Session
Chair: Bin Dai, HKUST, A601, HKUST, Kowloon, Hong Kong - PRC,
dbbudstar@gmail.com
1 - Stochastic Cost Estimation Approach for Full-Scale Reverse
Osmosis Desalination Plants
Seong-Hee Kim, Associate Professor, Georgia Institute of Technology,
765 Ferst Dr, Atlanta, GA, 30332, United States of America,
skim@isye.gatech.edu, Pyung-Kyu Park, Jae-Hong Kim,
Varun Gandhi, Pranay Mane, Hoon Hyung, Chuljin Park
We present a differential variational inequality framework to consider the
equilibrium patterns of oligopolistic markets through pollution taxes and quotas for
sustainability. An algorithm is proposed to compute the oligopolistic firms’
equilibrium output rate, shipping pattern, and pollution flow with or without the
central authority. A numerical example is also presented to illustrate the use of our
theory.
2 - Technology Base Second Tier Distribuitors Sustainability in Mexico
Guillermo Torres, PhD in Administration, Tecnologico De Estudios
Superiores De Coacalco, Av. 16 de Septiembre # 54, Coacalco de
Berriozàbal, 55700, Mexico, chapultepec19@hotmail.com,
Eduardo G. Hernandez-Martinez
A stochastic approach was developed to estimate the construction and operation
cost of a seawater reverse osmosis (SWRO) desalination plant. The stochastic cost
model was further coupled with a process simulation model that predicts
performance measures such as water production rate and produced water quality.
The case study demonstrates the effectiveness of the coupled model in ranking and
comparing a large number of design and operating conditions for the full-scale
SWRO plant.
At present, it has become increasingly hard for businesses to survive in a globalized
market, when traditional differentiators must adjust to new circumstances since
they are less efficient as opposed to new scenes. This study is focused on identifying
competitiveness of small business in Mexico, who are specialized in trading and/or
distributing computer equipment, that increasingly find it more difficult to compete
against the large chains.
2 - Self-Insurance: The Case of the Canadian Oil Sands
Kalinga Jagoda, Assistant Professor, Mount Royal University,
4825 Mount Royal Gate SW, Calgary, AB, T3E7N9, Canada,
kjagoda@mtroyal.ca, Pamini Thangarajah
3 - A Stochastic Linear Programming Model for the Management of
Emission Rights
Justyna Dyduch, Cracow University of Economics, Department of
Industrial and Ecological, ul. Rakowicka 27, 31-510 Kraków, Cracow,
Poland, dyduchj@uek.krakow.pl
In Canadian oil sands much of the negative publicity is around land pollution and
there are calls for establishment of disaster relief program to manage hazardous
events. Using the theory of public goods, we analyze the self insurance aspects of
such program and the efficient provision levels.
The management of emission rights means using them to cover enterprise’s
emissions, selling or buying them on the market, banking and borrowing them. We
describe a multi-stage recourse model that optimizes the production, the use and
acquisition of emission rights. The model is established to maximize enterprise’s
total profit.
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4 - Sustainable and Maintainable: An Equipment Maintenance Model
with Environmental and Economic Inputs
Thomas Sloan, University of Massachusetts Lowell, 1 University
Avenue, College of Management, Lowell, MA, 01854, United States
of America, Thomas_Sloan@uml.edu, Joseph Sarkis
Tutorial: Searching and Hiding on Networks
Cluster: Tutorials
Invited Session
An MDP model using traditional economic measures and environmental measures is
used to optimize equipment maintenance decisions. Increased deterioration leads to
more energy usage, more scrap, and greater environmental burdens. Maintenance
reduces these burdens but has environmental and economic impacts. The impacts of
using different cleaning solvents to perform maintenance are estimated using data
from the Toxic Use Reduction Institute (TURI).
Chair: J. Cole Smith, Professor, University of Florida, Industrial and
Systems Engineering, 303 Weil Hall, P.O. Box 116595, Gainesville, FL,
United States of America, cole@ise.ufl.edu
1 - Searching and Hiding on Networks
J. Cole Smith, Professor, University of Florida, Industrial and Systems
Engineering, 303 Weil Hall, P.O. Box 116595, Gainesville, FL,
United States of America, cole@ise.ufl.edu
■ WC05
The problem of deploying and controlling a set of searchers on a network to locate a
hidden target is referred to as a search game. There are countless variations of this
game, depending on, e.g., whether or not the target is mobile, and the searchers’
communication and control capabilities. This tutorial will examine classical results in
this field, discuss contemporary search literature, and explore research directions in
this field as driven by future security challenges.
Dynamic Programming/Control I
Contributed Session
Chair: Srinivasa Puranam, Rutgers University, 1 Washington Park,
Newark, NJ, 07102, United States of America, karti@pegasus.rutgers.edu
1 - Further Insight on Optimizing Taboo Criteria in Markov
Decision Processes
Michael N. Katehakis, Professor, Rutgers Business School,
1 Washington Park, Newark, United States of America,
mnk@andromeda.rutgers.edu, Srinivasa Puranam
■ WC07
Supply Chain Optimization II
Optimization of systems is often based on costs associated with the states of the
system. However, in many applications it is difficult to determine costs for all states.
In such situations, one could consider maximizing taboo criteria such as the taboo
mean return times for a propitiously defined set of taboo states. This is a hard
problem and well-known methods can not be applied. However, we can provide
further insight and heuristics for this problem.
Contributed Session
Chair: Haitao Li, University of Missouri - St. Louis, 229 CCB, One
lihait@umsl.edu
1 - Game Theoretic Analysis of Supply Chain
Satish Tyagi, Wayne State University, Department of Industrial,
Manufacturing Engineering, Detroit, MI, 48202,
United States of America, styagi.nifft@gmail.com, Kai Yang
2 - Risk-Averse Control Problem for Undiscounted Infinite Horizon
Markov Decision Models
Ozlem Cavus, Rutgers Center for Operations Research, 640
Bartholomew Road, Piscataway, NJ, 08854, United States of
America, ozlem_cavus@yahoo.com, Andrzej Ruszczynski
The aim of this paper is to exploit the salient features of Game Theory in modeling
and to investigate SC functioning under various alliances. In order to give a realistic
view to model, a comprehensive objective function has been formulated by
combining different objectives. This paper introduces a novel approach Gaussian
Particle Swarm Optimization which is embedded with beneficial attributes viz. (1)
Gaussian probability distribution, and (2) Time Varying Acceleration Coefficients.
The Markov risk measure is introduced and used to formulate risk-averse control
problems for finite and infinite horizon models by Ruszczynski. In this study, this
new concept is used to formulate and solve an infinite horizon insurance problem
where one of the control decisions is to purchase insurance. Furthermore, riskaversion is introduced for undiscounted infinite horizon Markov control models
with absorption.
2 - Measuring the Bullwhip Effect in the Supply Chain Based on the
Demand Forecasting Coordination Level
Seong-Hyun Nam, Associate Professor, University of North Dakota,
Management Department, Grand Forks, ND, 58202-8377,
United States of America, snam@business.und.edu
3 - Managing Data Quality Risk in Accounting Information Systems
Manuel Nunez, Associate Professor, School of Business, UConn,
2100 Hillside Road Unit 1041, Storrs, CT, 06269, United States of
America, mnunez@business.uconn.edu, Xue Bai, Jayant Kalagnanam
This paper studies the role of coordination in relation of the bullwhip effect. It seeks
to derive a bullwhip effect measure using a stochastic optimal control theory. In
particular, we measure how much the supply chain bullwhip effect mitigation
depends on the level of supply chain coordination of demand forecast and develop
the strategic coordination policy.
The quality of data contained in accounting information systems has a significant
impact on internal business decision-making and external regulatory compliance.
We present a methodology for managing the risks associated with the quality of
transactional data in accounting information systems. This methodology models the
error introduction and propagation process in transactional data flow, and finds
optimal control policies to mitigate data quality risks using a Markov decision
process.
3 - Heuristic Procedures for Biomass-to-Biorefinery Supply Chains
Ambarish Acharya, PhD Candidate, Mississippi State University, Dept
of Industrial & Systems Engineering, Mississippi State, MS, 39762,
United States of America, ama206@msstate.edu, Daniela Gonzales,
Sandra Eksioglu
4 - Vehicle Routing with Traffic Congestion and Drivers’ Driving and
Working Rules
Marco Schutten, University of Twente, Fac. Management and
Governance, P.O. Box 217, Enschede, 7500 AE, Netherlands,
m.schutten@utwente.nl, Leendert Kok, Erwin Hans, Henk Zijm
The objective of this research is modeling and solving coordinated biomass-tobiorefinery supply chain design and management problem. We discuss a number of
special cases of this problem where the location, capacity and number of facilities is
known. We propose solution procedures to solve the general problem and its special
cases.
We develop a solution method for the VRPTW, time-dependent travel times, and
driving hours regulations. The major difficulty of this VRPTW extension is to
optimize each vehicle’s departure times to minimize the duty time of each driver.
We propose a restricted dynamic programming heuristic for constructing the vehicle
routes, and an efficient heuristic for optimizing the vehicle’s departure times for
each (partial) vehicle route, such that the complete algorithm runs in polynomial
time.
4 - Optimizing the Supply Chain Configuration for
Make-to-Order Manufacturing
Haitao Li, University of Missouri - St. Louis, 229 CCB,
One University Blvd, St. Louis, MO, 63121,
United States of America, lihait@umsl.edu, Keith Womer
5 - Optimal Bidding in Sequential Auctions with Random
External Demand
Srinivasa Puranam, Rutgers University, 1 Washington Park, Newark,
NJ, 07102, United States of America, karti@pegasus.rutgers.edu,
Michael N. Katehakis
Configuring an MTO supply involves determining both sourcing and scheduling
supply chain activities to meet customer’s demand in a cost effective and time
efficient way. We develop an optimization model and algorithm for optimally
configuring MTO supply chains. Managerial insights are derived and discussed.
We consider the problem of sequentially bidding in N auctions of identical items
when items acquired are sold in a secondary market. The demand size and the sales
price are random variables with known distributions. The objective is to acquire
items through a sequence of auctions and sell them in the secondary market at
maximum expected profit. We present a Markov decision processes model for this
problem and study monotonicity properties of the optimal bids, for several cases of
interest.
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■ WC08
■ WC09
Facility Location I
Retail Operations and Assortment Planning
Contributed Session
Sponsored Session
Chair: Priyanka Verma, Indian Institute of Technology Kanpur, IME
Department, Kanpur, 208016, India, priyankav08@gmail.com
1 - A Location-allocation-local Search Procedure for Territory Design
with Multiple Balance Constraints
Roger Z. Ríos-Mercado, Universidad Autónoma de Nuevo León,
CIDET-FIME, AP 111 - F, Cd. Universitari, San Nicolàs de los Garza,
66450, Mexico, roger@yalma.fime.uanl.mx
Chair: Felipe Caro, UCLA Anderson School of Management,
110 Westwood Plaza, Suite B-420, Los Angeles, CA, 90095,
United States of America, fcaro@anderson.ucla.edu
1 - Dynamic Assortment Strategies for Variety-Seeking Consumers
Dorothee Honhon, University of Texas at Austin, IROM, B6500,
Austin, TX, United States of America,
Dorothee.Honhon@mccombs.utexas.edu, Gurhan Kok
In this talk, a commercial territory design problem motivated by a real-world
application in the bottled beverage distribution industry is addressed. A novel
location-allocation-local search algorithm is presented and fully evaluated over a
wide range of instances. The results indicate the excellent performance of some of
the procedure components. It also shown how the algorithm finds design plans of
significantly better quality than those currently handled by the company.
In this project, we first characterize the static optimal assortment for a retailer with
variety-seeking consumers. We then characterize the optimal assortment sets in the
dynamic strategy that offers possibly different assortments each period. We show
that it is possible to generate a high level of satisfaction at the customer level by
having a mixed assortment strategy.
2 - Hospital Location Planning in Singapore
Kok-Choon Tan, Assoc Prof, National University of Singapore, NUS
Bisiness School, 15 Kent Ridge Drive, Singapore, 119245, Singapore,
kokchoon@nus.edu.sg, Joe SIM
2 - Dynamic Assortment Customization with Limited Inventories
Fernando Bernstein, Duke University, 1 Towerview Dr., Durham,
NC, 27708, United States of America, fernando@duke.edu,
Gurhan Kok, Lei Xie
Singapore is currently served by 6 public hospitals which provide affordable and
good quality healthcare. This research aims to enhance the health ministry’s
capabilities in planning new acute and community hospitals, which are costly
investments. We will describe the use of Urban OR techniques to develop a decision
support system that allows policy makers to compare the impact among different
choices of new hospital locations with the corresponding sizes and capabilities.
We consider a retailer with limited inventories of a category of substitutable
products and heterogeneous customer preferences. Customers arrive sequentially
and the firm decides which subset of the products to offer to a customer depending
on the customer type, the inventory levels and the time-to-go in the season. We
show that limiting the choice set of some customers can significantly increase
profitability.
3 - Enabling Easy Consumer Access to Services and Products
Baris Hasdemir, UMASS, Isenberg School of Management,
Finance and Operations Management, Amherst, 01003,
United States of America, hasdemir@som.umass.edu, Agha Ali
3 - Dynamic Assortment Models: A Portfolio Approach
Felipe Caro, UCLA Anderson School of Management,
110 Westwood Plaza, Suite B-420, Los Angeles, CA, 90095,
United States of America, fcaro@anderson.ucla.edu, Rene Caldentey
Enabling better access to services for spatially dispersed populations is pertinent in
today’s fiscally constrained socio-political landscape. A network of centers provides
better access if the centers are located so as to serve maximal populations within
each of multiple threshold distances. Computational studies using a model with
distance differentiation of the population involving 1,829 model instances reveal
insights about possible access for the 224M people living in 23K places in the US.
We investigate optimal dynamic assortment planning strategies for a retailer with
limited shelf space. The retailer can choose among basic and fashion items with low
and high risk (and return) respectively. We present two models within this setting.
One is theoretical where we explicitly model the vogue trend as a stochastic process
that the retailer tries to follow. The second model has a similar objective but a much
simpler formulation intended for easy implementation in practice.
4 - Facility Location and Relocation Problem (FLRP-U)
Under Uncertainty
Ayse Durukan Sonmez, PhD Candidate, University of Houston,
Department of Industrial Engineering, Engr. Bldg 2, Houston, TX,
77204, United States of America, adurukan@uh.edu, Gino Lim
■ WC10
Track and Trace Technologies in Supply Chains
FLRP-U is a facility location and relocation problem that considers future demand
changes as well as uncertainties in number of future facilities. The objective is to
minimize the sum of the initial weighted distance and the expected future distance,
within a given budget for opening and closing of facilities. We propose a
decomposition algorithm that can produce near optimal solutions for FLRP-U. Our
numerical results compare the performance of our algorithm with exact solution
techniques.
Sponsored Session
Chair: Gary Gaukler, Texas A&M University, TAMU-3131, College Station,
United States of America, gaukler@tamu.edu
1 - Item-level RFID Tagging and Inventory Record Accuracy
John Aloysius, University of Arkansas, WCOB 226 University of
Arkansas, Fayetteville, United States of America,
JAloysius@walton.uark.edu, Bill Hardgrave, Sandeep Goyal
5 - Single/two Stage Warehouse Location Problem: Solution Technique
and Strong, Weak, Hybrid Formulations
Priyanka Verma, Indian Institute of Technology Kanpur, IME
Department, Kanpur, 208016, India, priyankav08@gmail.com,
RRK Sharma
Previous research has demonstrated that case-level RFID tagging can improve
inventory record accuracy for consumer packaged goods. The increased visibility
provided by item-level tagging however enables tracking items in-store right up to
the point-of-sale. We report the results of experiments in the field that investigate
the potential of item level tagging in the retail store.
For the single stage uncapacitated warehouse location problems, hybrid
formulations are shown to be the best performer against weak and strong
formulations for large sized problems. Vertical decomposition approach is presented
for the single and two stage capacitated warehouse location problem. Large sized
complex warehouse location problem is decomposed into the smaller and relatively
simpler versions of the capacitated plant location problems by the use of vertical
decomposition approach.
2 - The Impact of Supply Network and Product Characteristics on
Tracking Technology Assimilation
Rahul Basole, Tennenbaum Institute, Georgia Tech, 760 Spring Street
NW, Atlanta, GA, 30332, United States of America,
rahul.basole@ti.gatech.edu, Maciek Nowak
This research examines the influence of supply network and product characteristics
on the extent of tracking technology (TT) adoption and use. We develop and test a
theoretical model through a global survey of supply chain executives. Our results
provide insights into how factors such as product value, handling risk, and supply
network complexity impact the level of TT assimilation. This study yields important
implications for the management of emerging IT in a supply chain operations
context.
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WC13
3 - The Impact of Product Contamination in the Food Supply Chain
Vijaya Chebolu-Subramanian, Texas A&M University, 3131 TAMU,
cheb12@neo.tamu.edu, Gary Gaukler
■ WC12
In this talk we discuss the impact of product contamination in a food supply chain
(e.g., e. coli contamination of spinach). We consider a real world situation in which
a contaminated food product has entered a supply chain and is being sold at the
retailer. We develop a quantitative model to quantify the overall cost of the
contamination event and evaluate the effect of the product and supply chain
attributes on the performance metrics of the model.
Supply Chain
Sponsored Session
Retail Supply Chain Management
Chair: Sandra Transchel, The Penn State University, University Park, State
College, PA, United States of America, sxt37@psu.edu
1 - Multi-echelon Inventory System for E-Retailer Fulfillment Centers
Juan Li, Cornell University, Ithaca, NY, 14853, jl879@cornell.edu,
John Muckstadt
■ WC11
The customers of e-retailers have different timeliness requirements on order
delivery. The demand process has significant impact on designing the fulfillment
centers. In this paper, a multi-echelon system is designed for this type of system. We
describe an algorithm to compute the optimal order-up-to level for this system.
Supply Chain Issues & Sustainability
Sponsored Session
2 - Joint Inventory Pricing and Assortment Decisions for
Vertically Differentiated
Mrinmay Deb, Student, Penn State University, 462A Business
Building, University Park, State College, PA, 16802,
United States of America, mud166@psu.edu, Susan Xu
Chair: Chelliah Sriskandarajah, The University of Texas at Dallas, 800
West Campbell Road, SM30, School of Management, Richardson, TX,
75080, United States of America, chelliah@utdallas.edu
1 - Optimal Life Cycle Inventory Management
Burcu Keskin, Assistant Professor, University of Alabama, Alston
Hall, Tuscaloosa, AL, United States of America, bkeskin@cba.ua.edu,
Charles Schmidt
We determine the joint pricing, inventory, and assortment decisions of a retailer
stocking quality differentiated products. Consumers choose their first choice based
on the vertical choice model. We consider two cases: inventory is abundant (riskless
case) and inventory is finite (risky case) and find the optimal prices and optimal
assortments in each case.
We consider inventory replenishment of a product with nonstationary, stochastic
demand that moves probabilistically from one stage of the life cycle to the next,
each with its own demand and cost information, until the end-of-life. The planning
horizon is neither infinite nor of a known finite length. Via analytical analysis, we
show that stage-dependent base stock policy is optimal. Via numerical analysis, we
show the impact of not modeling the random product life on cost and inventory
levels.
3 - Joint Pricing and Inventory Decisions Under
Stockout-Based Substitution
Sandra Transchel, The Penn State University, University Park,
State College, PA, United States of America, sxt37@psu.edu,
Anna-Lena Beutel, Stefan Minner
2 - On the Tradeoff Between Remanufacturing and Recycling
Tharanga Rajapakshe, University of Texas at Dallas, 800 West
Campbell Road, SM30, School of Management, Richardson, TX,
75080, United States of America, tharanga@utdallas.edu,
Srinagesh Gavirneni, Milind Dawande, Chelliah Sriskandarajah
We consider a joint inventory and pricing problem for partially substitutable
products in a given assortment. Both price and inventory decisions have to be made
under demand uncertainty. Additionally, the retailer has to take into account that
customers are willing to substitute their first choice product if this is not available.
We present structural properties of the proposed model and provide managerial
insights into the interaction of pricing, stocking decision, and product
cannibalization.
Motivated by our interactions with two Dallas-based reverse-logistics firms, we
analyze the tradeoff between two well-known product-recovery approaches:
recycling and remanufacturing. Our analysis exploits the supply- and demand-side
implications as well as product design characteristics of these approaches. We
provide a complete theoretical characterization of the tradeoff and develop rich
insights on the influence of ability of sustainability and disposal costs.
■ WC13
3 - Inventory Models for Medium-size Depository Institutions Under the
New Federal Reserve Policy
Yunxia Zhu, The University of Texas at Dallas, 800 West Campbell
Road, SM30, School of Management, Richardson, TX, 75080,
United States of America, yunxia.zhu@student.utdallas.edu, Milind
Dawande, Chelliah Sriskandarajah
Managing Service Systems with Self-interested Actors
Sponsored Session
Chair: Eren Cil, University of Oregon, 1208 University of Oregon,
Lindquist College of Business, Eugene, OR, 97403-1208,
United States of America, erencil@uoregon.edu
1 - A Service Marketplace with Multiple Classes and Multiple
Skilled Agents
Eren Cil, University of Oregon, 1208 University of Oregon, Lindquist
College of Business, Eugene, OR, 97403-1208, United States of
America, erencil@uoregon.edu, Gad Allon, Achal Bassamboo
We study two new multi-period models — designed specifically to capture the
operations of a medium-size Depository Institution — that emerge from its objective
to minimize the total cost incurred in managing the inventory of cash over a finite
planning horizon under the new Federal Reserve policy. We develop several
managerial insights from a comprehensive test bed and demonstrate a procedure to
easily adapt the optimal solutions based on projected data to near-optimal real-time
solutions.
4 - Scheduling Robotic Cells Served by a Dual-Arm Robot
Manoj Vanajakumari, Texas A&M University, College Station, TX,
United States of America, manoj@entc.tamu.edu, Avanti Sethi,
Chelliah Sriskandarajah, Neil Geismar
We consider a service marketplace in which customers have different service needs.
Each customer can be served by either a group of agents specialized to cater
particular needs of that customer or a general pool of agents who can handle any
requests but not as competently as the specialized agents. We analyze how the selfinterested customers choose between the dedicated and the general service, and
characterize the response of the agents in the general pool to the customers’
choices.
We assess the benefits of implementing a dual-arm robot in a flow shop
manufacturing cell. The robot has the ability to tend two adjacent machines
simultaneously. We identify optimal sequences for two and three machine cells and
also derive structural results for cells with an arbitrary number of machines. For
cells processing different part-types, we completely analyze two-machine cells. For
each case we compare the productivity of single-arm and dual-arm robotic cells.
2 - Price Competition Under Multinomial Logit Demand Funcations with
Random Coefficients
Margaret Pierson, Harvard Business School, Morgan Hall, Boston,
MA, United States of America, mpp2002@columbia.edu,
Awi Federgruen, Gad Allon
We postulate a general class of price competition models with Mixed MNL demand
functions under affine cost. By imposing a natural upper bound for the price levels
of each firm, we characterize the equilibrium behavior of these models in the case
of single-product firms and then generalize the results to the multi-product case.
This work provides a justification for the many structural estimation methods which
require that equilibria correspond with the solutions to this system of FOC
equations.
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WC14
■ WC15
3 - Coordinating Diagnosis and Service in a Service Supply Chain
Mehmet Fazil Pac, PhD Candidate, Wharton School of Business,
University of Pennsylvania, 3730 Walnut Street, Jon M. Huntsman
Hall, Office 527.6, Philadelphia, PA, 19104, United States of America,
mpac@wharton.upenn.edu
Organization Theory I
Contributed Session
We consider a service consisting of two phases; diagnosis and service. Each phase is
provided by a self-interested agent. Diagnostic accuracy depends on the effort
exerted by the diagnosis agent. Investing more time in diagnosis leads to higher
valuation of the actual service by customers, however it also leads to lower
throughput and more congestion for the system. Using a queuing framework, we
analyze the agents’ diagnosis and pricing decisions under the presence of strategic
customers.
Chair: Theresa Edgington, Baylor University, One Bear Place, #98005,
Waco, 76798, United States of America, theresa_edgington@baylor.edu
1 - A Clustering Approach For Multi-Facility Location Problem
Cem Iyigun, Department of Industrial Engineering, Middle East
Technical University, Ankara, Turkey, iyigun@ie.metu.edu.tr,
Adi Ben-Isreal
4 - Service Control of a Queue Under Different Delay
Information Structures
Brent Dooley, Wharton School, 3730 Walnut St., 500 Jon M.
Huntsman Hall, Philadelphia, PA, 19104, United States of America,
dooleyb@wharton.upenn.edu, Noah Gans, Omar Besbes
A new clustering approach is proposed. The method is a generalization of Weiszfeld
method and applied for solving K facilities location problem. The problem is relaxed
using probabilistic assignments, and is decomposed into K single facility location
problems, that are coupled by the probabilities, and can be solved in parallel.
2 - Considering the Relationship Between Empowerment and
Resistance to Change
Nathan Culmer, The University of Iowa, 2800 UCC, Iowa City, IA,
52242, United States of America, nathan-culmer@uiowa.edu
We analyze the problem of profit-maximization for an M/M/1 queue with dynamic
service rate control when customers have access to varying degrees of state/policy
information. In particular, we examine customer equilibrium behavior and its
implications on optimal service rate policies.
Both psychological and team level empowerment have been shown to have
desirable effects in organizations while employee resistance to change can have
undesirable effects on organizational or work group progress. Interestingly, these
characteristics share some common theoretical elements. This paper considers
possible theoretical relationships between empowerment as a motivational construct
and the influence that empowerment can exert on employee resistance to change.
■ WC14
Supply Chain Management X
3 - Institutional Barriers to Application of Continuous Improvement
Processes From Safety to Energy Efficiency
Rodney Lacey, Lecturer, Univ of California Davis, Graduate School of
Management, One Shields Avenue, Davis, CA, 95616,
United States of America, rolacey@ucdavis.edu
Contributed Session
Chair: Jie Yang, Associate Professor, University of Houston-Victoria,
14000 University Blvd, Sugar Land, TX, 77479, United States of America,
jieuhv@gmail.com
1 - Mid-term Planning Coordination Between Maker and Retailer by
Capacity Reservation
Seung-Jin Ryu, Research Associate, Waseda University, 51-14-07, 34-1 Okubo, Shinjuku, Tokyo, 1698555, Japan, sjryu@aoni.waseda.jp,
Hisashi Onari
Historic institutional differences between the fields of safety and energy efficiency
could limit transfers of continuous improvement programs. Three differences of
commensuration (Espeland and Stevens, 1998) between lives and units of energy
are potential barriers: being efficient is commendable, rather than inefficiency
deplorable; moral value of efficiency gains varies across industries; and there are no
moral objections to making tradeoffs between efficiency and other goals.
Collaborative SCM is the collaborated initiatives among SC members to deal with
various problems over SC. It is the challenging issue, in high-tech industry,
especially experiencing severe market demand change, keeping the stable and
profitable operation level. We propose the mid-term planning coordination method
between maker and retailer by capacity reservation. Also, we verify strengths and
weaknesses of the proposed method by dynamic simulation with various business
environments.
4 - To Build or Break Away? Exploring the Antecedents of Category
Spanning Nanotechnology Innovation
Tyler Wry, U of Alberta, 3-23 Business Building, Edmonton, AB, T6G
2R6, Canada, twry@ualberta.ca
Category spanning has implications for innovation and institutional change. Still,
studies have focused primarily on its detrimental effects, eliding consideration of
causal antecedents. Examining the nanotube technology field, I argue that patterns
of linkage amongst categories enable spanning. Competing hazard rate models are
supportive. Further, I find these linkages are shaped endogenously by prominent
actors and condition the effects category richness, social networks, and social
influence.
2 - Transportation Pricing of a Truckload Carrier
Aysegul Toptal, Assistant Professor, Bilkent University, Department of
Industrial Engineering, Ankara, Turkey, toptal@bilkent.edu.tr,
Safa Bingol
In this study, we investigate the transportation pricing problem of a truckload
carrier in a setting that consists of a retailer, a truckload carrier and a less than
truckload carrier. Numerical evidence shows that the truckload carrier may increase
his/her gainings significantly through better pricing and there is further opportunity
of savings if the truckload carrier and the retailer coordinate their decisions.
5 - Evidentiary Analysis of Organizational Coordination and Questions
of Group Fragmentation
Theresa Edgington, Baylor University, One Bear Place, #98005,
Waco, TX 76798, United States of America,
theresa_edgington@baylor.edu
3 - Does Agility Matter in Improving Supply Chain Performance?
Evidence From a Transition Economy
Jie Yang, Associate Professor, University of Houston-Victoria, 14000
University Blvd, Sugar Land, TX, 77479, United States of America,
jieuhv@gmail.com
Analysis processes contribute to organizations by increasing their knowledge, which
is necessary to maximize decision-making and resolution outcomes. We investigate
whether a core group provides exemplary coordination by investigating its database.
Utilizing quantitative analysis, the evidence refutes this claim, contributing to the
literature by identifying eleven coordination process indicators.
This study develops and empirically tests a conceptual framework to investigate the
antecedents of manufacturers’ supply chain agility and the connection of their
agility with performance in an emerging economy. Drawing upon the information
theory, this study argues that technical (IT capability) and relational factors
(information sharing and trust, and operational collaboration) are the antecedents
of a manufacturer’s supply chain agility.
■ WC16
Flexible Manufacturing Systems
Contributed Session
Chair: Mabel Chou, Associate Professor, National University of Singapore,
BIZ 1 Mochtar Riady Building, #8-66, 15 Kent Ridge Drive, Singapore,
119245, Singapore, mabelchou@nus.edu.sg
1 - Value of Flexibility
Sanjeev Bordoloi, Associate Professor, University of St Thomas, 1000
LaSalle Ave, TMH 434, Opus College of Business, Minneapolis, MN,
55403, United States of America, sbordoloi@stthomas.edu
Economic justification of investments in flexibility has become increasingly
important. This paper tries to provide possible measures for flexibility so that
managerial decision making for flexibility can be validated. We offer a model that
minimized production planning costs and then use some of its characteristics for
flexibility measurements.
414
2 - Joint Maintenance and Operations Decision Making in Flexible
Manufacturing Systems
Merve Celen, University of Texas at Austin, 1 University Station
C2200, Austin, TX, 78712-0292, United States of America,
merve@mail.utexas.edu, Dragan Djurdjanovic
WC18
2 - Information Transmission and the Bullwhip Effect
Robert Bray, PhD Student, Graduate School of Business, Stanford
University, 311 Sheridan Ave, Palo Alto, CA, 94305,
United States of America, rlbray@stanford.edu, Haim Mendelson
We study the bullwhip effect in a sample of 4,689 public U.S. companies over 19742008. The traditional bullwhip is negative, but the “demand-uncertainty” bullwhip
is positive. We decompose the total bullwhip into deterministic and stochastic
components, and further decompose the latter by information transmission lead
times. Bullwhips come in several flavors—-firms can anticipate much, but not all, of
the bullwhip.
In semiconductor manufacturing, the dynamic interactions among operation types,
chamber degradations and wafer yields necessitate a joint decision making of
maintenance scheduling and product dispatching. To address this problem, we
devise an integrated decision making policy with the objective of maximizing an
adaptive profit function with respect to operation-dependent degradation models
and production target by using a metaheuristic method based on the results of
discrete-event simulations.
3 - Business Relationship Functions and Supply Chain Relationship
Quality: Evidence From China
Yongtao Song, School of Management, PO Box 2341, Xi’an Jiaotong
University, Xi’an, 710049, China, xjtusyt@gmail.com, Qin Su
3 - Dynamic Control of Closed Flexible Queueing Network with
Application to Shipbuilding
Fang Dong, Ph.D Candidate, University of Michigan, Industrial &
Operations Engineering, 1205 Beal Ave., Ann Arbor, MI, 481092117, United States of America, ppfang@umich.edu,
Mark Van Oyen, David Singer
This paper adopts a functional view to analyze the value that buyers attain from
buyer-seller relationships and investigates the links between business relationship
functions (BRF), supply chain relationship quality (SCRQ) and buyer’s performance.
The results indicate that BRF have a direct and an indirect effect on buyer’s
performance through the mediating effect of SCRQ. Moreover, the availability of
alternative suppliers has a moderating influence on the relationship between BRF
and SCRQ.
The U.S. Shipbuilding Industry is facing the challenge of building ships on-time and
at budgeted cost. We introduce operational flexibility to ship production to mitigate
the issues like high variability in production workload and low facility utilization.
We formulate this problem as a flexible, controlled closed queueing network with
CONWIP release policy. Under an effective control policy, the flexible system can
significantly reduce ship completion time, and improve workshop utilization.
4 - 3rd Party Logistics Provider Selection with Performance
Metrics and ANP
Orrin Cooper, University of Pittburgh, 233 Mervis Hall, Pittsburgh,
PA, 15260, United States of America, orc1@pitt.edu, Jennifer Shang,
Pandu Tadikamalla
4 - A Graph-theoretic Methodology for Deadlock Resolution in
Automated Manufacturing Cells
Venkatesh Angirasa, Research Scientist & Manager, Group for
Decision Technology Solutions, SETLabs, Infosys Technologies,
Electronics City, Hosur Road, Bangalore, 560100, India,
venkatesh_angirasa@infosys.com
Selecting a third party logistics provider with the Analytical Network Process (ANP)
allows one to measure the interrelated influences of performance metrics in the
supply chain. The criteria in the decision matrix are organized according to the
temporal stages or flow of a product through the supply chain. A general model is
presented and applied to case data and tested for robustness with detailed sensitivity
analysis.
We present a deadlock detection and resolution strategy for manufacturing cells
with alternate part routing. We distinguish between cells with centralized buffers
and those with dedicated I/O buffers for individual machines. A unified bipartite
graph of the part-machine relationship enables the detection and resolution scheme
in both cases. Resolution policies are developed to accommodate varying
manufacturing systems requirements. An efficient algorithm is proposed to manage
deadlocks.
■ WC18
Industry Applications
5 - Value of the Third Chain: Effect of Partial Production Postponement
on Process Flexibility
Mabel Chou, Associate Professor, National University of Singapore,
BIZ 1 Mochtar Riady Building, #8-66, 15 Kent Ridge Drive,
Singapore, 119245, Singapore, mabelchou@nus.edu.sg,
Geoffrey A. Chua, Chung Piaw Teo
Contributed Session
Chair: Fubin Qian, PhD Candidate, Molde University College,
Britvegen 2, N-6411, Fannestrandveien 76, 6416, Molde, Norway,
fubin.qian@himolde.no
1 - Dynamic Capacity Planning for Short Life Cycle Products
Saman Alaniazar, PhD Candidate, Wayne State University, 4815
Fourth St., Detroit, MI, 48202, United States of America,
saman.alaniazar@wayne.edu, Alper Murat, Ratna Babu Chinnam
Using a multi-item newsvendor model with second-stage supply and partial capacity
sharing, we discover that the flexibility loss of the 2-chain is no longer negligible
under partial postponement. For small systems, this loss can be as high as 20% to
30%. However, we find that by adding another layer of flexibility, a third chain, the
flexibility loss can be restored to the same level as 2-chain with full postponement.
We show that the value of the third chain extends even to very large systems.
We study capacity planning for short life cycle products. Given the non-stationary
and region-based nature of the demand in this type of products, our model employs
a hybrid-strategy of short-term demand forecasting and long-term demand
modeling to monitor amount and time of expansions. Moreover, we consider and
apply a risk model in the process of capacity planning. We report experimental
results based on an implementation of the model in an agent based system for
Tamagotchi Case.
■ WC17
2 - Optimizing Credit Lines
Lisa Kart, Director, Analytics, FICO, Austin, TX, 78704,
United States of America, lisakart@fico.com
Supply Chain, Practice and Empirics
Contributed Session
Chair: Orrin Cooper, University of Pittburgh, 233 Mervis Hall, Pittsburgh,
PA, 15260, United States of America, orc1@pitt.edu
1 - Key Metrics and Current Industry Practices in Supply
Chain Measurement
Ramesh Bollapragada, Associate Professor, College of Business, San
Francisco State University, 1600 Holloway Avenue, San Francisco,
CA, 94132, United States of America, rameshb@sfsu.edu, Calvin Lee,
Tuna Cencki
Over the past several years, FICO has helped banks optimize credit line decisions
using predictive and decision modeling in a framework of constrained optimization.
Hear about the approach, how the analytics were implemented, and the results
achieved for banks across the globe.
3 - The Industry Emergence Funnel: Towards a Conceptual Framework
for Public Sector Coordination, Investment Prioritization and
Strategy Development
Eoin O’Sullivan, University of Cambridge, Cambridge,
United Kingdom,eo252@cam.ac.uk
The paper identifies current business practices and key measurements in supply
chain performance management. Our survey based research indicates that supply
chain professionals give high importance to quality and reliability factors, increasing
company’s competitiveness, and not just to cost factors, while creating effective
supply chains. The research underlines that more steps need to be taken to connect
supply chain partners, and create models for the quantification of intangible metrics.
This paper introduces a conceptual framework for analyzing the emergence of novel
technology-based industries. We make the case for an industry-level analogue of
established, firm-level “funnel” models of innovation. The features of the proposed
framework are based on observed patterns of historical emergence of technologybased industries analyzed using roadmapping techniques.
415
WC19
4 - A Tabu Search Heuristic for Offshore Helicopter Routing Problem
with Focus on Passenger Safety
Fubin Qian, PhD candidate, Molde University College, Britvegen 2,
N-6411, Fannestrandveien 76, 6416, Molde, Norway,
fubin.qian@himolde.no, Irina Gribkovskaia, Gilbert Laporte, ÿyvind
Halskau
2 - Pricing and Timing of New Version Releases in the Presence of
Strategic Consumers
Shubin Xu, Lundquist College of Business, University of Oregon,
Eugene, OR, 97403, United States of America, sxu@uoregon.edu,
Michael Pangburn
We study a firm offering successive product versions. Due to ongoing R&D or
improving technology, each new version implies an opportunity cost associated with
continued use of the prior product. The firm decides the time between successive
introductions, and price. In turn, consumers strategically choose whether to
purchase or wait for a later version. We consider the firm’s profit maximizing policy
assuming a homogeneous market and then extend the analysis to address consumer
heterogeneity.
A mathematical model is proposed to improve passenger transportation safety by
minimizing the expected number of fatalities in offshore helicopter transportation.
Tabu search heuristics are developed. Both the mathematical model and heuristics
are capable of producing general solutions, namely solutions allowing a second visit
to installations. Computational results show that safety performance can be
significantly improved by introducing general solution strategy to helicopter routing
problem.
3 - Integrating Capacity Control Concepts into the Locate-to-OrderSystems of Automotive Manufacturers
Thomas Volling, Technische Universität Braunschweig, Institute of
Automotive Management and Industrial Production,
Katharinenstrasse 3, Braunschweig, 38106, Germany,
t.volling@tu-bs.de, Thomas S. Spengler
■ WC19
Dynamic Optimization in Energy Pricing
Lead times in the automotive industry exceed customers’ expectations for the
delivery of new cars. As a consequence, most manufacturers have established hybrid
order fulfillment strategies combining elements from build-to-order and build-tostock (BTS) production. The focus of the contribution is on the BTS share of
vehicles. A capacity control is developed to support the allocation of preconfigured
cars to customer requests. Assignments are evaluated based on product specific
opportunity costs.
Sponsored Session
Chair: Canan Uckun, University of Chicago, 5807 South Woodlawn
Avenue, Chicago, IL, 60637, United States of America,
cuckun@chicagobooth.edu
1 - Market Power Analysis in Electricity Markets with
Time-of-use Pricing
Emre Celebi, University of Waterloo, Department of Management
Sciences, 200 University Ave. West, Waterloo, ON, N2L 3G1, Canada,
ecelebi@engmail.uwaterloo.ca, David Fuller
4 - Dynamic Optimal Design for Sequential Online Auctions
Xi Chen, University of Washington, Box 352650, Industrial
Engineering, Seattle, 98195, United States of America,
chenxi07@uw.edu, Archis Ghate, Arvind Tripathi
Retailers often conduct a sequence of online auctions to sell identical items as a
revenue generation and inventory management tool. We show that under a second
order condition on the single- auction expected revenue function, a threshold policy
is optimal for inventory scrapping and a monotone staircase with unit jump policy is
optimal for lot sizing. This condition is met in all common auction mechanisms. We
investigate an extension where the minimum bid is also optimized.
We propose variational inequality models for electricity markets with time-of-use
(TOU) pricing. The demand response is dynamic in the model through a
dependence on the lagged demand. Different market structures are examined
within this context. With an illustrative example, the welfare gains/losses are
analyzed after an implementation of TOU pricing scheme over the single pricing
scheme. Also, break-up of a large supplier into smaller parts is investigated.
2 - Enabling Price-Responsive Demand Management in
Electricity Markets
Hung-po Chao, ISO New England, hchao@iso-ne.com
5 - Product Upgrades and Pricing with Strategic Consumers
Oben Ceryan, Ross School of Business, University of Michigan,
701 Tappan St, Ann Arbor, MI, 48109, United States of America,
oceryan@umich.edu, Ozge Sahin, Izak Duenyas
The traditional approach to demand response suffers from the missing property right
problem that could undermine electricity market efficiency. A multi-settlement
retail tariff solves the problem by allowing each customer to establish a contractbased baseline through demand subscription before joining a demand response
program. A two-settlement system with demand subscription and dynamic default
rate facilitates price-responsive demand for general consumer benefits.
We consider a firm that allows upgrading of customers purchasing a lower quality
product to a higher quality product if there is excess demand for the former and
excess capacity for the latter. We investigate the optimal pricing and capacity
decisions in the presence of strategic consumers that consider product prices as well
as upgrade possibilities when choosing which product to purchase.
3 - An ADP Approach to Decomposing Smart Grid Pricing Problems
Canan Uckun, University of Chicago, 5807 South Woodlawn
Avenue, Chicago, IL, 60637, United States of America,
cuckun@chicagobooth.edu, Dan Adelman
■ WC21
Service Contract and Incentive Design
In the electricity smart grid, millions of homes will receive price signals
simultaneously. We can formulate the problem of optimizing prices through time as
a dynamic programming problem, containing state information for each home.
However, the problem has such large scale that it is intractable using standard
solution methods. We propose a new decomposition approach to solving this
dynamic program approximately.
Sponsored Session
Chair: Hermann Jahnke, Professor, Bielefeld University,
Universitaetsstrasse 25, Bielefeld, 33615, Germany, hjahnke@wiwi.unibielefeld.de
1 - After-sales Contract Analysis for Service Supply Chains
Dong Li, Rotterdam School of Management, Erasmus University, P.O.
Box 1738, Rotterdam, Netherlands, dli@rsm.nl, Yugang Yu, Nishant
Mishra, Xinguo Ming
■ WC20
Pricing and Revenue Management II
The multiple types of contract of the service supply chain may cause conflicting
incentives. We use a game-theoretic frame to model the behavior of a service supply
chain, and compare the different type of contracts and show that how the
parameters affect the optimal solutions. We also find out that the inefficiency can be
coordinated with a revenue-sharing performance based contract.
Contributed Session
Chair: Oben Ceryan, Ross School of Business, University of Michigan,
701 Tappan St, Ann Arbor, MI, 48109, United States of America,
oceryan@umich.edu
1 - Dynamic Revenue Management with Nonlinear Pricing
Wei Wei, Case Western Reserve University, Dept of Operations,
Weatherhead School, 10900 Euclid Ave, Cleveland, OH, 44106-7235,
United States of America, wei.wei@case.edu, Matthew J. Sobel
2 - Incentive Design in Industrial Product Service Systems:
A Simulation Study
Partha Datta, Assistant Professor, IIM Calcutta, Diamond Harbour
Road, Joka, Calcutta, 700104, India, parthapriya.datta@gmail.com
Powerful incentives and risks are normally used in industrial service contracts to
transfer risks to measure compliance with performance measures. This paper studies
the uncertainty in service delivery driven by the agreed contract type and incentive
mechanism using agent based discrete event simulation model under multiple
scenarios.
We compare linear pricing with multi-part tariffs in a class of dynamic revenue
management models with stochastic iso-elastic demand. Each period a firm sets
multiple prices corresponding to a multi-part tariff and decides how much inventory
to hold back for sale later. There is a nearly explicit myopic optimum that can be
computed easily. The results exploit the homogeneity of an associated Markov
decision process. We illustrate the results with a numerical example.
416
3 - Lower Price Limits for Flat-fee Service Contracts Under Risk
Hermann Jahnke, Professor, Bielefeld University, Universitaetsstrasse
25, Bielefeld, 33615, Germany, hjahnke@wiwi.uni-bielefeld.de,
Jan Thomas Martini
■ WC23
Many manufacturers of capital equipment offer services under flat-fee service
contracts. We address the determination of lower price limits for such contracts.
Under these contracts, the service providers assume part of the customer’s risk. We
focus on the impact this risk has on price limits. Our modeling tool, almost
stochastic dominance, allows us to examine decision making under risk without
precisely knowing the decision makers’ risk preferences as well as a multi-person
decision context.
Sponsored Session
WC24
Service Management and Virtual Enterprise
Chair: Munish Goyal, Research Staff Member, IBM Research, AC2 L1,
ISB, GACHIBOWLI, Hyderabad, AP, 500032, India,
mungoyal@in.ibm.com
1 - Value Based Dynamic Resource Allocation in a Service Cloud
Munish Goyal, Research Staff Member, IBM Research, AC2 L1, ISB,
GACHIBOWLI, Hyderabad, AP, 500032, India,
mungoyal@in.ibm.com, M Rammohan Rao
4 - Towards a Theory of Service Improvisation
Enrico Secchi, Clemson University, 128 Cochran Rd. Apt. 1,
Clemson, SC, 29631, United States of America,
esecchi@clemson.edu, Aleda Roth
Cloud computing is a pool of virtualized computer resources which can be
dynamically added or removed in response to changing business demands while
meeting service level agreements at the minimal energy or operational cost. In this
work, we develop relative value based dynamic resources allocation strategies where
a unit of resource is allocated to a customer request with the highest value above
the energy value threshold at any time. Algorithm is supported with numerical
results.
This paper examines the role of improvisation in the context of service delivery
systems. Drawing from organizational improvisation literature and service
operations and marketing, we develop antecedents and consequences of service
improvisation. First, we define the concept of service improvisation. Second, we
highlight the importance of the interplay between planning and execution. Finally,
we develop a theoretical link between service delivery and the emergence of service
innovations.
2 - Negotiation Based Completion Risk Management for
Virtual Enterprise
Min Huang, Professor, Northeastern University, Box 135#,
Northeastern University, Shenyang, 110004, China,
mhuang@mail.neu.edu.cn, Hongyu Jiang, W.H. Ip, Qing Wang,
Xingwei Wang
■ WC22
Service System Design and Effectiveness
In the view of the distribution feature of decision-making in a virtual enterprise, a
novel decision-making framework based-on negotiation is proposed for the
completion risk management of VE. Under this framework, according to the
characteristics of the problem, the evaluation mechanism of the owner is designed
based on PERT, and then the concession tactic is proposed. The example analysis
shows that this framework can achieve effective risk management.
Sponsored Session
Chair: Adelina Gnanlet, Assistant Professor, California State University,
Fullerton, 800 N. State College Blvd, Dept of Mgmt, Fullerton, CA,
92832, United States of America, agnanlet@fullerton.edu
1 - Impact of Labor and Capacity Flexibilities on Quality and a
Financial Performance of Hospitals
Adelina Gnanlet, Assistant Professor, California State University,
Fullerton, 800 N. State College Blvd, Dept of Mgmt, Fullerton, CA,
92832, United States of America, agnanlet@fullerton.edu,
Muge Yayla-Kullu, Chris McDermott
3 - Service Parts Inventory Control Under Obsolescence
Cerag Pince, PhD Candidate, Erasmus University, Burg. Oudlaan 50,
Rotterdam, 3000 DR, Netherlands, pince@few.eur.nl,
Rommert Dekker, Hans Frenk
We consider a single location inventory system of a slow moving item where
Poisson demand rate drops to a lower level at a known future time. Under the
assumptions of full backordering and fixed lead time, we incorporate obsolescence
into a one-for-one policy with the option to reduce the base stock level in advance.
We show that when obsolescence can be foreseen, early adaptation of base stock
levels leads to important savings.
To reduce costs and meet variable demand, service firms frequently cross-train
employees and use flexible capacity in capital intensive service firms. Higher crosstraining is cost-effective but may not provide adequate quality of service due to
learning effects. Flexible capacity may not be conducive to provide highest level of
quality for certain demand segments. We determine the effects of cross-training and
flexible capacity on quality and financial performance of hospitals.
■ WC24
2 - Impact of Task Complexity on Productivity in Professional Services
Anil Akpinar, IE Business School, C/ Maria de Molina 12, Madrid,
28006, Spain, aakpinar.PhD2010@alumno.ie.edu, Fabrizio Salvador
Decision Making for Wildfire Response and Evacuation
In this paper we explore the effect of task complexity on the flexibility efficiency
trade-off in knowledge worker productivity. Using a longitudinal data from one of
the largest multinational technology and consulting firm, we provide empirical
evidence that while specialization and variety jointly drives productivity, their
effects are quite distinct for varying levels of task complexity.
Sponsor: Public Programs, Service and Needs
Sponsored Session
3 - More with Less - Service Resource Scheduling by Time
Capacitated Splits
Pasi Porkka, Assistant Professor, Aalto University School of
Economics, P.O. Box 21220, Helsinki, Fin-00076, Finland,
porkka@hse.fi
Chair: Nada Petrovic, Graduate Student, Physics Department,
Broida Hall, UC Santa Barbara, Santa Barbara, CA, 93106-9530,
United States of America, petrovic@physics.ucsb.edu
1 - Dynamic Resource Allocation in Wildfire Suppression
Nada Petrovic, Graduate Student, Physics Department, Broida Hall,
UC Santa Barbara, Santa Barbara, CA, 93106-9530, United States of
America, petrovic@physics.ucsb.edu, David Alderson, Jean Carlson
The balancing of resource time used for production or services and for capacity
consuming set-ups is critical for the realistic planning of high capacity utilization.
We combine the allocation of shared resources, the time-based splitting of tasks and
variable set-ups in mobile service operations. The potential for substantial capacity
time savings is demonstrated. Extensions and solution approaches for realistic
applications are discussed.
Wildfire response demands dynamic decision tools because fires and suppression
evolve simultaneously. Time delays can lead to larger fires and thus greater demand
for resources. We capture this tension using a queuing model that treats fire
progression as a birth and death process, with rates that incorporate intrinsic fire
dynamics and suppression. Using this framework we explore trade-offs in
effectiveness and time delay of response.
4 - The Impact of Service Quality Variation on Service Quality,
Operational Efficiency, and Performances
Hong-il Kim, PhD Candidate, Korea University Business School,
Anam-dong, Seongbuk-gu, Seoul, 136-701, Korea, Republic of,
itlime@korea.ac.kr, Hosun Rhim, Shijin Yoo, Daeki Kim
2 - A Space-Time Flow Optimization Model for
Neighborhood Evacuation
David Alderson, Assistant Professor, Naval Postgraduate School,
Naval Postgraduate School, 1411 Cunningham Road, Monterey, CA,
93943, United States of America, dlalders@nps.edu,
William Langford
We investigate how service quality variation affects service quality, operational
efficiency, and business performances. Data of branch operation in a retail bank is
collected. Perceived service quality of customers is surveyed with SERVERPF
questionnaire. HLM (Hierarchical Linear Modeling) and DEA (Data Envelopment
Analysis) are used.
We model the evacuation of vehicles in a residential neighborhood using a spacetime network flow representation. Our model solves for “best case” evacuation
routes and clearing times, as could be identified and implemented by a central
authority. Our models are large but can be solved efficiently and quickly. We apply
this model to the Mission Canyon neighborhood near Santa Barbara, California, and
contrast our results to a previous simulation-based study.
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WC25
■ WC26
3 - Influence of Information Networks on Collective
Evacuation Dynamics
Danielle Bassett, Postdoctoral Research Associate, University of
California Santa Barbara, 6213 Broida Hall, Santa Barbara, CA,
93106, United States of America, dbassett@physics.ucsb.edu, Jean
Carlson, David Alderson
Interface Between Efficient Data Collection and
Flexible Data Modeling
Sponsor: Data Mining
Sponsored Session
The collective behavior of humans during an evacuation is a poorly understood,
complex phenomenon which we model as a combined centralized-decentralized
consensus problem, influenced by information flow over layers of technological,
social, and geographic networks. An individual’s belief regarding disaster severity is
constantly updated until reaching a decision threshold. We describe differential
dynamics over these layers, indicating sensitivity of human decision-making to
information origin.
Chair: Peter Qian, University of Wisconsin-Madison, 1300 University Ave,
Madison, WI, 53706, United States of America, peterq@stat.wisc.edu
1 - Improvement on Cross-Validation via Sliced Statistical Design
Xinwei Deng, Visiting Assistant Professor, University of WisconsinMadison, Department of Statistics, 1300 University Ave., Madison,
WI, 53706, United States of America, xdeng@cs.wisc.edu, Peter Qian
4 - Making Emergency Evacuation Decisions with
Uncertain Information
Emily Craparo, Naval Postgraduate School, Glasgow Hall Room 226,
Monterey, CA, United States of America, emcrapar@nps.edu,
David Alderson, Jean Carlson
A training data is often used to construct models to predict the future response. The
cross-validation is a traditional method to compare different models and assess their
prediction performance. It can provide a nearly unbiased estimate of prediction
error, but can be with high variability. In this work, we proposed a novel sliced
statistical design strategy to improve the performance of cross-validation,
substantially outperforms the usual method in various classification problems.
In emergency situations, time-critical decisions must be made based on uncertain
information. Situational awareness is improved through additional observation of
the threat; however, observation delays action. We consider an individual decisionmaker who faces an uncertain threat and who must decide when (and whether) to
perform a costly evacuation. We model this evacuation decision problem using
dynamic programming and establish optimal evacuation policies under a variety of
cost models.
2 - Regularized REML for Estimation and Selection of Fixed and
Random Effects in Linear Mixed-Effects Mo
Sijian Wang, Assistant Professor, University of Wisconsin, Madison,
1300 University Ave., Madison, WI, 53706, United States of America,
wangs@stat.wisc.edu
In the practice of LMM, inference on the structure of random effects component is
of great importance not only to yield proper interpretation of subject specific effects
but also to draw valid statistical conclusions. In this paper, we propose a novel
method of regularized restricted maximum likelihood to select fixed and random
effects simultaneously in the LMM. We also investigate large sample properties for
the proposed estimation, including the oracle property.
■ WC25
Transportation, Planning II
Contributed Session
3 - Consistent Selection of the Number of Clusters via
Clustering Stability
Junhui Wang, University of Illinois at Chicago, 851 S Morgan St,
Chicago, IL, 60607, United States of America, jwang@math.uic.edu
Chair: Chi Xie, Research Fellow, The University of Texas at Austin,
chi.xie@mail.utexas.edu
1 - Composite Variable Formulation for Truckload Relay
Network Design
Hector Vergara, Graduate Research Assistant, University of Arkansas,
4207 Bell Engineering Center, Fayetteville, AR, 72701,
United States of America, hvergara@uark.edu, Sarah Root
In cluster analysis, one major challenge is to estimate the number of clusters. In this
talk, I will present a novel selection criterion that is applicable to all kinds of
clustering algorithms. The key idea is to select the number of clusters such that the
resulting clustering algorithm has the smallest instability, which measures its
robustness against the sampling randomness. Numerical examples and asymptotic
selection consistency will be discussed.
Full truckload (TL) trucking usually considers a Point-to-Point dispatching method.
Alternatively, multi-zone dispatching under a network configuration of relay points
can be used to improve driver retention. We propose a new mathematical
formulation for strategic relay network design that places relay points and
determines driver routes. Our model minimizes total costs while considering
operational constraints such as driver tour length and load circuity within the
variable definition.
4 - Optimal Supersaturated Design for Variable Selection via Lasso
Dadi Xing, PhD Student, Purdue University, 224-7 Arnold Drive,
hwan@purdue.edu, Hong Wan, Yu Zhu
In the supersaturated design(SSD) study, most existing criteria for constructing
optimal SSD are motivated and further justified from the estimation perspective. We
will propose a number of optimality criteria for the construction of SSD from the
perspective of variable selection with Lasso. The properties of these criteria will be
discussed. A computing algorithm will be used to construct such optimal SSD, and
examples of simulation and real applications will also be presented.
2 - An Optimal Cycle Length Model for Feeder Transit Services
Shailesh Chandra, Student, Department of Civil Engineering, Texas
A&M University, 3136 TAMU, College Station, 77843-3136, United
States of America, chandrashailesh@gmail.com, Chung-Wei Shen,
Luca Quadrifoglio
A simulation based generic model has been derived for estimating optimal cycle
lengths of a demand responsive transit “feeder” services. For input parameters such
as the shape size and daily demand density of an area, the success of this model has
been validated by a case study.
■ WC27
Network Optimization II
3 - Transportation Planning for Squatter Developments
Hani Al-Naghi, PhD Candidate, American University of Beirut,
P.O.Box 11-0236, Riad El Solh, Beirut 11, Beirut, Lebanon,
haa31@aub.edu.lb, Nabil Nehme
Contributed Session
Chair: Nan Jiang, Student, University of Texas, Austin, 1 University
Station C1761, ECJ 6.2, Austin, TX, 78712, United States of America,
njiang@mail.utexas.edu
1 - A Reformulation-Linearization Technique for the Two-level Facility
Location Problem
Youngho Lee, Korea University, Sungbuk Ku Anam Dong 5-1, Seoul,
Korea, Seoul, Korea, Republic of, shadowpp@korea.ac.kr,
Gigyoung Park
This paper addresses urban transportation planning issues related to squatter
developments and their integration with the surrounding areas. A general
framework encompassing all criteria related to social, economics, land use and
political aspects, is formulated and applied to selected case studies in Lebanon.
4 - A Primal-dual Mathematical Programming Framework for Traffic
Assignment Problems
Chi Xie, Research Fellow, The University of Texas at Austin,
chi.xie@mail.utexas.edu, Travis Waller
In this paper, we deal with an two-level facility location problem based on the tree
topology. In particular, we develop a model for this problem and apply the
reformulation-linearization technique (RLT) to construct various enhanced
tightened versions of the proposed model. And we derive necessary and sufficient
conditions for a family of some inequalities to be facet-defining.
Traffic assignment problems have been formulated as mathematical programs,
variational inequalities, complementarity systems, and fixed-point models. It is well
known that the last three modeling techniques all provide a common functional
form for modeling different traffic assignment problems. This talk presents a
uniform primal-dual mathematical programming framework, which can be used to
accommodate a variety of traffic assignment problems.
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2 - Continous Network Design Problem with Emission Constraint
Nan Jiang, Student, University of Texas, Austin, 1 University Station
C1761, ECJ 6.2, Austin, TX, 78712, United States of America,
njiang@mail.utexas.edu, ManWo Ng, Travis Waller
WC30
2 - Upgrading Policy After Redesign of a Component for
Reliability Improvement
Kurtulus Oner, Assistant Professor, Eindhoven University of
k.b.oner@tue.nl, Geert-Jan Van Houtum, Gudrun P. Kiesmüller
In this paper, a traffic network design model with emission constraint and its
solution method are presented. The resulting solutions are a set of capacity
improvements to a given network, for a given demand, subject to user-specified
budget constraints and emission constraint and resulting in minimal system total
cost. Application results prove this model decreases system emission and provide
information useful for planning road network improvements under air quality
constraints.
We introduce a model for studying the following two upgrading policies that an
OEM may implement after the redesign of a component: (i) Upgrade all
preventively at time 0, (ii) Upgrade one-by-one correctively. We develop a problem
formulation for the comparison of the two policies and perform exact analysis. We
conduct a numerical study and derive insights on the optimality of the policies.
3 - Component Reliability Criticality or Importance Metrics for Systems
with Degrading Components
David Coit, Associate Professor, Rutgers University, Industrial &
Systems Engineering, 96 Frelinghuysen Rd., Piscataway, NJ, 08854,
United States of America, coit@rutgers.edu, Hao Peng, Qianmei Feng
■ WC28
This paper proposes new importance measures (IMs) for systems with either
independent or dependent degrading components. As functions of time, the
proposed IMs can provide timely feedback on the critical components based on the
observed degradation. The correlation between components and the dependency of
failure thresholds are considered through multivariate distributions. Numerical
examples show that the proposed IMs are effective in assessing criticality of
degrading components.
Manufacturing Process Optimization
Sponsored Session
Chair: Roshan Vengazhiyil, Coca-Cola Associate Professor, Georgia
Institute of Technology, Industrial and Systems Engineering, Atlanta, GA,
30332, United States of America, roshan@isye.gatech.edu
1 - An Interactive Method to Multiresponse Surface Optimization Based
on Pairwise Comparisons
Dong-Hee Lee, Pohang University of Science and Technology,
Department of Industrial and Management, Pohang, Korea, Republic
of, princeps@postech.ac.kr, Kwang-Jae Kim, Murat Köksalan
4 - Maintenance Policy Based on MultiCriteria Decision Aiding
Cristiano Cavalcante, Federal University of Pernambuco, Caixa
Postal, 5125, Cep 52070960, Recife, PE, 52070960, Brazil,
cristianogesm@gmail.com, Adiel Almeida
Maintenance planning is very sensitive to characteristics of the system, the context
and the objectives of the decision maker. Regarding this problem, the most common
analyses consist of evaluating the cost rate function. But, in some specific contexts
the consequence of failures has distinct dimensions, which are difficult to represent
by only one criterion (monetization). Thus, we discuss models based on MCDA
(MultiCriteria Decision Aiding) approach, in order to support maintenance
planning.
In multiresponse surface optimization, responses are often in conflict. To obtain a
satisfactory compromise, the preference information of a decision maker (DM) on
the tradeoffs among the responses should be incorporated into the problem. We
propose an interactive method where the DM provides preference information in
the form of pairwise comparisons. The results of pairwise comparisons are used to
estimate the preference parameter values in an interactive manner. The method is
effective in that a highly satisfactory solution can be obtained.
2 - Analysis of Computer Experiments with Functional Response
Ying Hung, Rutgers, Camden, NJ, United States of America,
yhung@stat.rutgers.edu, Roshan Vengazhiyil, Shreyes Melkote
■ WC30
We develop an efficient implementation of kriging for analyzing functional
responses. The main contribution of this paper is to develop a two-stage model
building procedure and a general framework which can be used irrespective of the
data structure. The methodology is illustrated using a computer experiment
conducted for optimizing residual stresses in machined parts.
Statistics/Quality Control II
Contributed Session
Chair: Xuan Huang, Assistant Professor, University of Alabama at
Birmingham, 345 Lincoln Ave., Apt 115, Amherst, MA, 01002, United
States of America, xuan@som.umass.edu
1 - Comparison of Ozone Levels Among Five Cities using
Control Charts
Gautam Eapi, PhD Student, University of Texas at Arlington, Civil
Engineering, Box 19308, Arlington, TX, 76019, United States of
America, gautam.raghavendra@gmail.com, Melanie Sattler,
Mostafa Ghandehari
3 - New Variable Selection Methods Under Engineering
Inequality Constraints
Hin Kyeol Woo, Georgia Institute of Technology, 765 Ferst Drive,
Atlanta, GA, 30329, United States of America, hinkyeol@gatech.edu,
Andres Hernandez, Jye Chyi Lu, Martha Grover
This presentation discusses new variable selection methods under engineering
inequality constraints. A case study of nanoparticle synthesis with a solubility
constraint motivates and illustrates the research. Simulation experiments explore
properties of the proposed method.
Ozone is one of the six criteria pollutants, as specified by the USEPA. Statistical
quality control can be helpful in improving quality. In this paper, data for ozone
levels of five different cities across the U.S. is analyzed by using control
charts.Control charts are used to compare the cities. In addition, out of control data
points are discussed.
■ WC29
2 - A Bayesian Approach to Estimating Market Implied Risk
Neutral Densities
James Delaney, Assistant Professor, Temple University, Department
of Statistics (006-12), 1810 N 13th Street, Philadelphia, PA, 191226012, United States of America, james.delaney@gatech.edu,
Marc Sobel
Maintenance Management and Service Logistics
Sponsored Session
Chair: Alaa Elwany, Assistant Professor, Eindhoven Unviersity of
Technology, Eindhoven, Netherlands, elwany@tue.nl
Contemporaneous prices of financial derivatives provide much information about
the so-called “market implied risk neutral distribution” (MIRND) of the security that
underlies those derivatives. Here we propose a Bayesian model to provide the
regularity necessary for estimating a MIRND that corresponds to a set of options’
prices. We provide details on a much more generally useful technique for simulating
from the very complex posterior distribution of this model’s parameters.
Co-Chair: Nagi Gebraeel, Associate Professor, Georgia Tech, 765 Ferst Dr.,
Atlanta, United States of America, nagi.gebraeel@isye.gatech.edu
1 - Modified Block Replacement Can Outperform Age Replacement in
Terms of Spare Parts Ordering
Rommert Dekker, Erasmus University Rotterdam, Burg Oudlaan 50,
Rotterdam, 3062 PA, Netherlands, rdekker@ese.eur.nl
3 - Orthogonal Polynomial and Saddle Point Approximations for Sums
of Non-identical Binomial Random Variables
Aysun Taseli, Research Assistant, Northeastern University,
360 Huntington Avenue, 334 Snell Engineering, Boston, 02115,
United States of America, aysunt_qpl@yahoo.com, James Benneyan
It is well known that age replacement outperforms block replacement as better
information on the likelihood of failures is used. Yet block replacement allows a
more appropriate ordering of spare parts as replacements can be planned in time. In
this presentation we present a study which shows that the better spare parts
planning can offset the advantages of age replacment. The study also reveals what
kind of inventory policies are useful in this respect.
We compare performance and discuss relative advantages of saddle point
approximations (SPA) and cumulant based orthogonal polynomial expansions for
estimating the convolution of non-identical binomial distributions. Some important
healthcare and service applications of this distribution involve methods that require
repetitive computation of probabilities. Both SPA and a normalized Gram-Charlier
expansion are shown to be accurate and fast compared to the exact PDF and Monte
Carlo estimation.
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WC31
4 - Beta Model-based Control Chart for Fraction Monitoring with
Correlated Process Variables
Michel Anzanello, Professor, Federal University of Rio Grande do
Sul, Av. Osvaldo Aranha, 99, Porto Alegre, 90.035-190, Brazil,
michel.anzanello@gmail.com, Angelo Sant’Anna, Carla ten Caten
5 - Optimization Models for Online Adaptive Radiotherapy
Chunhua Men, University of California, San Diego, 3855 Health
Sciences Dr. #0843, La Jolla, CA, 92093, United States of America,
cmen@ucsd.edu, Steve Jiang
Traditional treatment plan optimization models based on a snapshot of the patient’s
anatomy prior to treatment are not suitable for online adaptive radiotherapy (ART)
which allows real-time treatment adaptations based on the current patient anatomy.
In this work, we develop and evaluate various optimization models for online ART.
To obtain real-time treatment plans, we implement the algorithms on GPU. Tests on
clinical cancer cases showed the effectiveness and the efficiency of these models.
Although widely used to monitor processes where quality characteristics vary with
adjustments in control variables, model-based control charts’ efficiency is
jeopardized by high correlated control variables. Our method integrates Principal
Components Analysis to Beta model-based control charts to overcome such
limitation. Sensitivity Analysis using Monte Carlo simulation validates the method.
5 - Dimension Reduction of Multivariate Autocorrelated Processes
Xuan Huang, Assistant Professor, University of Alabama at
Birmingham, 345 Lincoln Ave., Apt 115, Amherst, MA, 01002,
United States of America, xuan@som.umass.edu
■ WC32
In traditional multivariate literature, Principal Components Analysis (PCA) is the
standard tool for dimension reduction. For autocorrelated processes, however, PCA
fails to take into account the time structure information. It is arguable that PCA is
still the best choice. In this presentation I propose an enhanced dimension reduction
method which by design takes into account both cross-correlation and
autocorrelation information. I demonstrate it through case studies and simulations.
Computational Stochastic Programming
Sponsored Session
Chair: Shabbir Ahmed, Associate Professor, Georgia Institute of Tech,
765 Ferst Drive NW, Atlanta, GA, United States of America,
sahmed@isye.gatech.edu
1 - A Preconditioning Technique for Schur Complement Systems
Arising in Stochastic Optimization
Mihai Anitescu, Computational Mathematician, Argonne National
Laboratory, Math and Computer Science Division, 9700 S Cass Ave,
Argonne, IL, 60439, United States of America, anitescu@mcs.anl.gov,
Cosmin Petra
■ WC31
Health Care, Therapy and Treatment
Contributed Session
Chair: Chunhua Men, University of California, San Diego, 3855 Health
Sciences Dr. #0843, La Jolla, CA, 92093, United States of America,
cmen@ucsd.edu
1 - Identifying and Quantifying Protein Values for Obtaining
Cancer Biomarkers
Chaitra Gopalappa, PhD Student, University of South Florida, 4202 E
Fowler Ave, Tampa, United States of America, chaitrag@gmail.com
We discuss a parallel interior-point method for stochastic programming that uses a
Schur complement mechanism. We propose a stochastic preconditioner to improve
scalability. The spectral analysis of the preconditioned matrix indicates an
exponential clustering of the eigenvalues around 1. The numerical experiments
performed on the relaxation of a unit commitment problem show good
performance, in terms of both the accuracy of the solution and the execution time.
2 - Models and Formulations for Optimization with Multivariate
Stochastic Dominance Constraints
James Luedtke, University of Wisconsin-Madison, 1513 University
Av., Madison, WI, United States of America, jrluedt1@wisc.edu,
Benjamin Armbruster
Identifying proteins that are only produced in the cancerous state of cells (cancer
biomarkers) can lead to its use as a diagnostic tool for early detection of cancer. The
task prior to detecting biomarkers (proteins that distinguish cases from controls),
i.e., identifying and quantifying the amount of all proteins, is an analytically
challenging task that requires mathematical models. We present the analytical
challenges and the mathematical models.
Multivariate stochastic dominance constraints provide an interesting modeling tool
for problems having multiple stochastic objectives. Recently proposed models use
extensions of the notion of positive linear stochastic dominance, but appear
computationally challenging to use. We propose to use a different notion of
dominance, based on expected utility theory, and present linear and integer
programming formulations for the corresponding problem.
2 - Retrofitting Tissue and Cell Banking: Best Practices and Emerging
Business Models
Katrina Nordstrom, Professor, Aalto University School of Science and
Technology, Department Biotechnology and Chemical technol,
Kemistintie 1A 16100 Aalto, Espoo, Finland,
katrina.nordstrom@tkk.fi, Marko Narhi, Petri Lehenkari,
Ari P.J. Vepsalainen, Olli Natri, Mika Pietila
3 - Learning Price Functions in Cournot Games
Uday Shanbhag, Asst. Professor, University of Illinois at Urbana
Champaign, Urbana, Il, United States of America,
udaybag@illinois.edu, Sean Meyn, Hao Jiang
The study explores “retrofitting” of blood banking by development of business
models based on best practices for collection, processing, storage and delivery of
cells and tissues. Plausible business models examine production of bone marrow,
umbilical cord blood stem cells and hematopoietic stem cells. A framework is also
specified for classifying and evaluating the capabilities and hurdles of supply chains
for living products for safe and traceable future products and therapies.
We consider a regime where firms compete in a Nash-Cournot game without the
knowledge of the precise parameters of the price functions. We show that the
resulting trajectory can be characterized. Convergence of the learning update
scheme is examined in deterministic and stochastic regimes.
3 - Turkey Disposal and Recycling Network Design Model for
Drug Industry
Ayse Gunes, Assistant Specialist, Industrial Engineer, Scientific and
Technical Research Council of Turkey (TUBITAK), 06100
Kavaklidere, Ankara, Turkey, ayse.gunes@tubitak.gov.tr,
Bahar Ozyoruk
■ WC33
Optimization Strategies for Real-World Applications
Sponsored Session
In Turkey, to determine the tendency of people, we first have made a survey related
to drug use, recycling, etc. with military personnel. We have developed a model that
provides waste disposal and recycling of paper in the minimum cost. In the
developed model, human and environmental health, hazardous waste disposal and
recycling for reuse are discussed and the model are solved with GAMS program.
This study includes case study, it is important for healthcare logistics and global
health topics.
Chair: Eva Lee, Professor & Director, Georgia Institute of Technology,
Center for Operations Research in Medici, Industrial & Systems
Engineeriing, Altanta, GA, 30332-0205, United States of America,
eva.lee@gatech.edu
1 - On the Simultaneity of Row and Column Generation
Jon Petersen, PhD Student, Georgia Institute of Technology,
765 Ferst Drive NW, Atlanta, GA, 30309, United States of America,
Petersen@gatech.edu, Ellis Johnson
4 - Linearity Effects in Brachytherapy Treatment Planning
Asa Holm, PhD Student, Linköpings Universitet, Matematiska
institutionen, Linköpings universitet, Linköping, 58183, Sweden,
asa.holm@liu.se, Torbjörn Larsson, Asa Carlsson Tedgren
While both constraint generation and column generation have been successfully
employed in solving practical real-world problems, they are often thought of as
being mutually exclusive. The efficacy of solving large-scale models can be improved
by using these two principles concurrently. We propose a new method for doing so,
and present computational results to validate our approach.
Modern optimization techniques for inverse planning of HDR brachytherapy makes
it possible to efficiently calculate dose plans. On of the tenets of such techniques is
the use of linear penalty functions. Plans generated with these techniques tend to
have a few dwell positions that dominate the solution, however physicians prefer
homogeneous plans. In this talk we show that one reason for the long dwell times is
the linear penalties and introduce a solution that reduces the effects of linearity.
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2 - Audience Space Aggregation for Ad Planning
John Turner, University of California - Irvine, The Paul Merage
School of Business, Irvine, CA, 92697, United States of America,
john.turner@uci.edu
■ WC35
Whether serving ads on web pages or in newer media such as video games,
targeting constraints lead to a combinatorial explosion in the number of audience
segments. Using an aggregation heuristic for large transportation problems, we
allocate impressions to ad campaigns at an appropriate granularity. Computational
results show that a little bit of disaggregation goes a long way: Near-optimal
solutions are achieved despite a high degree of aggregation.
Sponsored Session
WC36
Advances in Anomalous Diffusion III
Chair: Mark Meerschaert, Michigan State University, Department of
Statistics and Probability, East Lansing, MI, United States of America,
mcubed@stt.msu.edu
1 - Approximation of Tempered Operator Stable Processes
Boris Baeumer, University of Otago, Department of Mathematics and
Statistics, Dunedin, New Zealand, bbaeumer@maths.otago.ac.nz,
Mihaly Kovacs
3 - Constraint Optimal Selection Techniques (COSTs) for
Linear Programming
H. W. Corley, IMSE Department, The University of Texas at
Arlington, Arlington, TX, 76019, United States of America,
corley@uta.edu, Jay Rosenberger, Goh Saito
Operator stable processes are characterised by the scaling matrix H and mixing
measure M. By randomly choosing a direction and then generating a onedimensional jump distance, the resulting process lies in the domain of attraction of
the operator stable process. All tempered processes lie in the domain of attraction of
a Gaussian. We show that for some tempered op-stable processes the speed of
convergence of the approximant to the tempered process is faster than the
convergence to the Gaussian.
We present a Constraint Optimal Selection Technique (COST) for efficiently solving
large-scale nonnegative linear programming problems. We provide a geometric
interpretation of the COST and computational comparisons with the CPLEX primal
simplex, dual simplex, and barrier algorithms.
■ WC34
2 - Cauchy Problems Solved by Running Subordinate Processes
Erkan Nane, Assitant Professor, Auburn University, 221 Parker Hall,
Auburn, AL, 36849, United States of America, ezn0001@auburn.edu
C - Room 7, Level 3
Optimization on Graphs
Subordinated Markov processes will be studied. These are obtained by taking
Markov processes and replacing the time parameter with other processes such as
Brownian motion, symmetric stable process, an inverse of a stable subordinator, or
local time of an stable process of index between 1 and 2. We obtain frational
Cauchy problems or Cauchy problems involving the powers of the generator of the
Markov Process by running these subordinated Markov processes.
Sponsored Session
Chair: Doug Altner, Assistant Professor, United States Naval Academy,
United States of America, altner@usna.edu
1 - Integer Programming Techniques for Matroid Circuit Problems
John Arellano, PhD Student, Rice University, 6100 Main St. MS 134,
Houston, TX, 77030, United States of America, jda2@rice.edu,
Illya Hicks
3 - Space-time Duality for Fractional Diffusion
Mark Meerschaert, Michigan State University, Department of
Statistics and Probability, East Lansing, MI, United States of America,
mcubed@stt.msu.edu, Boris Baeumer, Erkan Nane
Fractional diffusion equations govern scaling limits of random walk models. The
limit process is a stable Levy motion that models the jumps, subordinated to an
inverse stable process that models the waiting times. Using Zolotarev duality, we
relate the density of a spectrally negative stable process with index $1<\alpha<2$ to
the density of the hitting time of a stable subordinator with index $1/\alpha$, and
thereby unify some recent results in the literature.
Although some combinatorial optimization problems associated with matroids can
be solved in polynomial time, finding particular circuits in matroids is an NP-hard
problem. It is related to compressive sensing and finding the degree of redundancy
of sensor networks. In this talk, we attempt to solve these types of problems to
optimality using integer programming techniques and present computational results.
2 - Over Restriction of Network Expansion Big M Constraints
Kael Stilp, Georgia Institute of Technology, 765 Ferst Drive, NW,
Atlanta, GA, United States of America, mstilp3@isye.gatech.edu,
Ozlem Ergun, Pinar Keskinocak
4 - A Sex Talk: The Matchmaking Paradox
Iddo Eliazar, Professor, Holon Institute of Technology, P.O. Box 305,
Holon, 58102, Israel, eliazar@post.tau.ac.il
We discuss a multi period network expansion model where flow capacities are bigM constrained and nodes have supply and demand of commodities. The objective is
to minimize unsatisfied demand over all of the periods. We show computational
results behind restricting the M value to infeasible values as a means of speeding up
computation and achieving better solutions. To further understand the results we
discuss theoretical reasonings for the occurrence.
Medical surveys regarding the number of heterosexual partners per person yield
different female and male averages - a result which, from a physical standpoint, is
impossible. In this talk we establish a statistical model, based on random
attractiveness levels, which explains the aforementioned “matchmaking paradox”.
Our analysis concludes when, and when not, are surveys capable of well-estimating
the female and male averages.
3 - Coverings and Matchings in r-Partite Hypergraphs
Doug Altner, Assistant Professor, United States Naval Academy,
United States of America, altner@usna.edu, Paul Brooks
■ WC36
We present a few results regarding matchings and coverings in r-partite
hypergraphs. First, we present an alternate proof showing the integrality gap of the
standard BILP for r-dimensional matching is at least r-k where k is the smallest
positive integer such that r-k is a prime power. Second, we prove r-dimensional
covering is NP-hard for intersecting hypergraphs. Third, we prove a few upper
bounds on the covering number of a special class of intersecting hypergraphs that
are not balanced.
Education II
Contributed Session
Chair: Helene Caudill, Associate Professor of Management, St. Edward’s
University, 3001 South Congress Avenue, Austin, TX, 78704, United
States of America, helenec@stedwards.edu
1 - Simulating Student Flow Through a College of Business for Policy
and Structural Change Analysis
Robert Saltzman, Professor, San Francisco State University,
1600 Holloway Ave, College of Business, San Francisco, CA, 94132,
United States of America, saltzman@sfsu.edu, Theresa Roeder
Many public higher education institutions are trying to facilitate student graduation
even as institutional resources decline. We describe a model that simulates the flow
of undergraduates through a large public college, allowing changes in curriculum
policy, prerequisites, and staffing capacity to be tested prior to implementation.
Output measures include expected time to degree and graduation rates. The model
is used to experiment with both actual and potential scenarios facing the college.
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2 - A Simple Management Tool to Increase High School Track
Team Participation
Sambhavi Lakshminarayanan, Assistant Professor, Medgar Evers
College - CUNY, S-Building, Department of Business Admin, 1637
Bedford Avenue, Brooklyn, NY, 11225, United States of America,
sLakshminarayanan@mec.cuny.edu, Ashwin Acharya
3 - On Pro-rata Pricing Strategy for Extended Product Warranties
Raja Jayaraman, Postdoctoral Research Fellow, University of
Arkansas, Industrial Engineering, Bell 4207, Fayetteville, AR, 72701,
United States of America, rjayaram@uark.edu, Timothy Matis
Product warranties play a challenging and decisive role in today’s dynamic business
environment. Several strategies and models have been proposed assuming fixed cost
associated with various repair actions available to the manufacturer towards
rectifying product failures. In this presentation we shall address pro-rata pricing and
its overall effect towards minimizing expected cost for products carrying extended
warranties.
Convincing busy high school students to make a significant time commitment to
participate in athletics is a challenge. However, schools and athletic coaches consider
it highly desirable, if not necessary, for students to participate in athletic activities.
This paper discusses an approach developed by the senior members of the track
team at an academically focused high school to increase team numbers and
retention.
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3 - Teaching Business Statistics using Participatory Learning Methods
in a Multicultural Setting
Mark Ferris, Saint Louis University, 3674 Lindell Blvd, Room 457,
Saint Louis, MO, 63104, United States of America, ferrisme@slu.edu,
Reuven Levary
Theory and Applications in Copositive Programming
(Joint Cluster ICS)
Sponsored Session
Teaching pedagogy in business schools emphasize participatory learning methods
such as class discussion, group problem solving and case studies. The predominant
teaching methods for international students may not include a participatory
component, rather it is a system that emphasizes the teacher as the prime source of
knowledge. A strategy for ensuring the contribution of international students in a
participatory learning environment for statistics was developed, implemented and
evaluated.
Chair: Samuel Burer, Associate Professor, University of Iowa, S346
Pappajohn Business Building, Iowa City, IA, 52242-1994,
United States of America, samuel-burer@uiowa.edu
1 - New Approximations for Copositive Matrices
Samuel Burer, Associate Professor, University of Iowa, S346
Pappajohn Business Building, Iowa City, IA, 52242-1994,
United States of America, samuel-burer@uiowa.edu, Hongbo Dong
4 - Undergraduate and Graduate Students’ Perception about
Web-Enhanced and Online Courses
Hiral Shah, Assistant Professor, St Cloud State University, 720 Fourth
Ave S - ECC 101, St Cloud, MN, 56301, United States of America,
hashah@stcloudstate.edu, Devang Mehta
We introduce a new hierarchy of inner approximations of the copositive matrices.
The distinguishing feature of the hierarchy is its recursive nature, which deals with
smaller (but more) matrices as the recursive depth increases. For fixed depth, the
resulting inner approximation is a polynomially sized linear-semidefinite program.
The purpose of this study was to compare the perceptions of students about
completely online courses against web-enhanced courses. Data were collected from
both graduate and undergraduate students enrolled at two different higher
education institutions. The results of this study will enable instructors to modify
their teaching styles using either of these methods of teaching.
2 - Mixed Zero-One Linear Programs Under Objective Uncertainty:
A Completely Positive Representation
Chung Piaw Teo, Professor, National University of Singapore, NUS
Business School, BIZ1 8-72, NUS, 15 Kent Ridge Drive, Singapore,
119245, Singapore, bizteocp@nus.edu.sg, Zhichao Zheng,
Karthik Natarajan
5 - What is Academic Quality? A Comparison of Traditional and Adult
Students’ Perceptions
Helene Caudill, Associate Professor of Management, St. Edward’s
United States of America, helenec@stedwards.edu
We analyze mixed 0-1 linear programs under objective uncertainty using a moment
based approach, assuming descriptive statistics of the objective coefficients are
known, but not the exact form of the distribution. Our main result shows that
computing the supremum of the expected optimal objective value of such problem
is a completely positive program. The result is extended to objective coefficients over
Euclidean space, uncertain moments and more complicated objective functions.
There are numerous definitions of academic quality, but the one that I believe
affects student satisfaction and faculty reputations most often is the perception of
what students believe to be “quality in the classroom.” With responses from over
250 students, the results indicate that students focus on three main areas: the
credentials of the faculty member, the usefulness of the materials and assignments,
and the communication skills of the faculty member.
3 - Separating Doubly Nonnegative and Completely Positive Matrices
Kurt Anstreicher, Professor, University of Iowa, Department of
Management Sciences, Iowa City, IA, 52242, United States of
America, kurt-anstreicher@uiowa.edu, Hongbo Dong
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Completely Positive (CP) matrices can be used to formulate a variety of NP-Hard
problems. A natural issue in the optimization setting is to separate a given Doubly
Nonnegative (DNN) but non-CP matrix from the CP cone. We describe
constructions for such a separation that apply to 5x5 DNN but non-CP matrices, as
well as to larger matrices with block structure. Computational results illustrate the
ability of these procedures to generate improved bounds on difficult problems.
Applied Probability
Contributed Session
Chair: Raja Jayaraman, Postdoctoral Research Fellow, University of
Arkansas, Industrial Engineering, Bell 4207, Fayetteville, AR, 72701,
United States of America, rjayaram@uark.edu
1 - The Action Gambler and Equal-sized Wagering
David Hartvigsen, Professor, University of Notre Dame, 354 Mendoza
College of Business, Notre Dame, IN, 46556-5646, United States of
America, Hartvigsen.1@nd.edu
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Column Generation in Integer Programming
Sponsored Session
A gambler, with a bankroll B, faces a sequence of n identical, independent, win-lose
bets. When the total amount wagered (the total action) must be at least B, we show
that wagering B/n on each bet maximizes the expected utility of the final bankroll
iff the probability of winning a single bet is at most some p* (which is an explicit
function of B, n, and the utility function).
2 - Optimal Sequential Selection of a Unimodal Subsequence From a
Random Sample
Alessandro Arlotto, University of Pennsylvania, 3730 Walnut Street,
500 Jon M. Hunstman Hall, Philadelphia, PA, 19104, United States
of America, alear@wharton.upenn.edu, J. Michael Steele
Chair: Wilbert Wilhelm, Professor, Texas A&M University, Department of
Industrial and Systems Eng, TAMUS 3131, College Station, 77843-3131,
United States of America, wilhelm@tamu.edu
1 - A Stabilized Dynamic Constraint Aggregation/Column Generation
Method for the MDVSP
Guy Desaulniers, Ecole Polytechnique de Montréal and GERAD, CP.
6079, Succ. Centre-ville, Montréal, Canada,
Guy.Desaulniers@polymtl.ca, Pascal Benchimol, Jacques Desrosiers
The length of the longest unimodal subsequence in a random sample of size $n$ is
known to be asymptotic to $2\sqrt{2n}$. We study the sequential version of the
same problem in which, at every decision time $k\in\{1,...,n\}$, a decision-maker
has to select or reject the current observation in order to form a unimodal
subsequence of maximal expected length. We show that this expected length is
asymptotic to $2\sqrt{n}$.
In a column generation context, dynamic constraint aggregation that reduces the
number of constraints in the master problem was recently introduced to reduce
degeneracy. Dual variable stabilization is also effective at reducing the number of
column generation iterations. In this talk, we present a method that combines both
techniques and we report computational results for the multi-depot vehicle
scheduling problem.
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2 - Partial Path Column Generation for the Vehicle Routing Problem
Mads Jepsen, PhD., Technical University of Denmark,
Produktionstorvetbygn. 424, Kgs. Lyngby, 2800, Denmark,
makj@man.dtu.dk, David Pisinger, Björn Petersen
4 - Telling Value Stories with Value Diagrams
Somik Raha, Student, Stanford University, 1329 Park Drive #12,
Mountain View, CA, 94040, United States of America,
somik.raha@gmail.com
This paper presents a column generation algorithm for the Capacitated Vehicle
Routing Problem (CVRP). The Set Partitioning model with elementary routes, have
shown superior results. However, algorithms for solving the pricing problems do not
scale well. We suggest to relax the constraint that ‘each column is a route’ into
‘each column is a part of the giant tour’. This way, the length of the partial path can
be bounded and a better control of the size of the solution space is obtained.
We will examine how decision diagrams currently tell value stories, and propose
“Value Diagrams” to tell richer value stories that help clarify the value frame, create
mutual understanding on value and inform our value thinking in decision diagrams.
We will show through case studies how this can help us make decisions that are
aligned with our values.
3 - Unified Branch-Cut-and-Price for Routing and Scheduling
Marcus Poggi de Aragao, PUC-Rio, R. M. S. Vicente 225, Rio de
Janeiro, Brazil, poggi@inf.puc-rio.br, Eduardo Uchoa, Artur Pessoa
5 - A Simple Interval-Valued Decision Tree
Kash Barker, Lecturer, University of Oklahoma, 202 W. Boyd,
kashbarker@ou.edu
We extend the 1978 Picard-Queyranne approach to routing and sheduling
problems. The resulting Branch-Cut-and-Price adds a number of families of valid
inequalities described on variables from the original as well as on the ones from
extended formulations. Several variants of these problems are tackled with minor
adaptations. We address stabilization and performance issues. A wide range of
experimental results are presented. Finally, the generality and the evolution of the
approach is discussed.
Important to decision making is recognition of what today’s decisions have on
future options. An oft-used tool to aid in this problem is the decision tree. To
address situations when uncertainty arises in the metrics associated with different
decision paths, a simple decision tree is developed for uncertain parameters where
only bounds, not distributions, are known. Single- and multiobjective trees are
discussed.
4 - A Branch-and-cut Equivalent to Branch and Price
Wilbert Wilhelm, Professor, Texas A&M University, Department of
Industrial and Systems Eng, TAMUS 3131, College Station, 778433131, United States of America, wilhelm@tamu.edu, Deepak Warrier
■ WC41
Metaheuristics I
Branch and price is a leading approach to solve integer programs but suffers from
serious shortcomings, including converging slowly, failing to indicate it if prescribes
tighter bounds than the linear relaxation of the original problem, and failing to
readily incorporate cutting planes to tighten bounds. This paper describes a branchand-cut equivalent that prescribes the same bounds but overcomes these
shortcomings. Computational tests compare the effectiveness of the two approaches.
Contributed Session
Chair: Heidi Taboada, Assistant Professor in Industrial, Manufacturing and
Systems Engineering, Univeristy of Texas at El Paso, 500 W. University
Ave., El Paso, TX, United States of America, hataboada@utep.edu
1 - A New Evolutionary Algorithm Based on Adaptive Echolocation
Heidi Taboada, Assistant Professor in Industrial, Manufacturing and
Systems Engineering, Univeristy of Texas at El Paso, 500 W.
University Ave., El Paso, TX, United States of America,
hataboada@utep.edu, Karla Gutierrez
■ WC40
Decision Analysis IV
A new evolutionary algorithm that is based on the principle of echolocation, also
called biosonar is presented. This principle is active in numerous animals such as
bats. These animals use it as radar in order to find food, obstacles or locate objects.
The algorithm developed uses the radar method in order to explore the search space
to obtain optimal solutions. The new method is tested on the well-known single
objective redundancy allocation problem.
Contributed Session
Chair: Kash Barker, Lecturer, University of Oklahoma, 202 W. Boyd,
kashbarker@ou.edu
1 - Optimal Pricing, Modularity Level and Consumer Return for MC
Products using Uncertainty
Na Liu, The Institute of Textiles and Clothing, The Hong Kong
Polytechnic University, Hunghom, Kowloon, Hong Kong, Hong
Kong, Hong Kong - PRC, 08900900r@polyu.edu.hk, Jason Choi
2 - A Solution Method for the Constrained Level of Repair
Analysis Problem
Jose Espiritu, Assistant Professor in Industrial Engineering,
Univeristy of Texas at El Paso, 500 West University Avenue, El Paso,
TX, 79902, United States of America, jfespiritu@utep.edu,
Carlos Ituarte-Villareal
Mass customization (MC) is a pertinent industrial practice. MC retailers can gain
substantial advantages if return is considered. We study the optimal decisions under
a mean-variance analytical formulation. Structural properties are revealed and the
closed-form optimal solutions are derived. Sensitivity analysis is subsequently
conducted to explore how the risk sensitivity and other parameters affect the
optimal decisions. Counter-intuitive findings are obtained and insights are
generated.
A Level of Repair Analysis model, determines the most cost-effective
maintenance/replacement policy for each component within a system. In the
present research we develop a heuristic approach to solve the Level of Repair
Analysis considering budget constraints to indicate the optimal maintenance levels
at which items will be removed, repaired and replaced to meet operational
standards in a least optimal cost.
2 - Determining the Objective-based Feasibility of Installing a Sewage
Treatment Plant at a University
Mario Chew, Full Time Teacher, Technological Institute of Superior
Studies of Coacalco, Av. 16 de septiembre No. 54, Cabecera,
Municipal, Coacalco, Edo. de Mexico, México D.F., 55700, Mexico,
mchew@tesco.edu.mx, Verónica Velàzquez
3 - Tabu Search with Strategic Oscillation for a Maximum Dispersion
Territory Design Problem
Jabneel R. Maldonado-Flores, Universidad Autonoma de Nuevo
Leon, CIDET-FIME, AP111-F, Cd. Universitaria, San Nicolàs de los
Garza, NL, 66450, Mexico, jabneelmf@gmail.com,
Roger Z. Rìos-Mercado, José Luis Gonzàlez Velarde
A typical feasibility analysis of a Waste Water Treatment Plant (WWTP) calculates
economical or technical metrics, which are used to decide if the WWTP is to be
installed. If the fundamental objectives of the decision maker aren’t technical or
economical, such an analysis is not satisfactory; this is the case when a University
contemplates acquiring a WWTP. Here, we use Keeney’s Value-Focused Thinking to
incorporate the fundamental objectives of a University to the feasibility analysis of a
WWTP.
We address a districting problem motivated by the application of the WEEE
recycling directive in the European Union. In contrast to classical territory design,
maximum territory dispersion is sought for avoiding the creation of monopolies
forbidden by law in some countries. A tabu search with strategic oscillation is
proposed and evaluated over a wide range of instances with very promising
empirical results.
4 - Bicriteria Optimization of Energy Efficient Placement and Routing in
Heterogenous Sensor Networks
Mustafa Baydogan, Research Assistant, Arizona State University,
1802 E Randall Dr. Apt 3, Tempe, AZ, 85281, United States of
America, mbaydoga@asu.edu, Nur Evin Ozdemirel
3 - Using Decision Analysis to Model the Triune Relationship of Supply,
Demand, and Price
Jeff Stonebraker, Assistant Professor, North Carolina State University,
College of Management, Raleigh, United States of America,
jeff_stonebraker@ncsu.edu
We locate different type of sensors and route data generated to a base station under
two conflicting objectives: minimization of network cost and maximization of
network lifetime by satisfying connectivity and coverage requirements as well as
sensor node and link capacity constraints. We propose formulations and use an
exact solution approach to find Pareto solutions and develop a multiobjective GA to
approximate the efficient frontier, as the exact solution requires long computation
times.
Bayer was deciding whether to develop the third generation product used in the
treatment of hemophilia A. Bayer also wanted to right size its production capacity to
meet the demand while maximizing profitability. We use decision analysis to model
Bayer’s supply-demand-price conundrum.
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5 - An Evolutionary Approach Based on Viral Replication for Solving
Combinatorial Optimization Problems
Claudia Valles, MS student, The University of Texas at El Paso, 500
W. University Av., El Paso, TX, United States of America,
cevalles@miners.utep.edu, Heidi Taboada
Cost Effectiveness Models in Health Care
Sponsored Session
A new algorithm that mimics the performance of viruses is presented. The
replication mechanism as well as the hosts’ infection processes are used to develop
this new metaheuristic.The problem presented to show the performance of the
proposed algorithm is the multiple objective redundancy allocation problem. The
solution to this multiobjective problem is a set of Pareto-optimal solutions.
Chair: Greg Zaric, Associate Professor, Ivey Business School,
1151 Richmond St., London, Canada, gzaric@ivey.uwo.ca
Co-Chair: David Hutton, Stanford University, Palo Alto, CA, United States
of America, billdave@stanford.edu
1 - Cost Effectiveness of a Safe Consumption Site in Toronto, Canada
94035, United States of America, evaenns@stanford.edu, Greg Zaric,
Jennifer Jairam, Ahmed Bayoumi
■ WC42
Optimization and Scheduling for Supercomputers
The establishment of a safe consumption site (SCS) in Toronto, Canada has been
proposed to reduce the spread of disease through the sharing of drug use
equipment. We developed a compartmental model of the spread of HIV and
hepatitis C through populations of drug users and non-drug users matching those of
the Toronto area. We account for geographically disparate drug user groups and
mixing patterns between them, as well the influence of a centralized SCS on drug
user mixing behavior.
Sponsor: Optimization/Computational Optimization and Software (Joint
Cluster ICS)
Sponsored Session
Chair: Xueping Li, Assistant Professor, University of Tennessee, 408 East
Stadium Hall, Knoxville, TN, 37996, United States of America,
Xueping.Li@utk.edu
1 - Making Software Maintenance More Efficient on Kraken, the 1st
Academic Petaflop Computer
Mark Fahey, Scientific Computing Group Leader, National Institute
for Computational Sciences, 1 Bethel Valley Road, P.O. Box 2008 MS
6173, Oak Ridge, TN, 37831, United States of America,
mfahey@utk.edu
2 - Cost-Effectiveness of Stockpiling Masks and Respirators for the
Next Influenza Pandemic
David Hutton, Stanford University, Palo Alto, CA,
United States of America, billdave@stanford.edu, Nayer Khazeni
Surgical masks were used Mexico during the initial outbreak of the 2009 pandemic
influenza (H1N1). Several countries are stockpiling masks to use in future
pandemics. We use mathematical models of influenza disease spread to determine
the minimal necessary effectiveness and compliance to make stockpiling of masks
effective and cost-effective in an influenza pandemic. We compare these results with
other mitigation strategies involving pharmaceuticals.
The National Institute for Computational Sciences is the newest NSF High
Performance Computer center delivering 600 millions compute hours yearly to the
TeraGrid and is the 3rd fastest machine on the Top500. I will describe Kraken’s
capabilities and then talk about some infrastructure to (1) improve software
installation and maintenance and (2) track library usage by all the users; both with
the ultimate goal of improving the user experience while simultaneously make
NICS more efficient.
3 - Cost-Effectiveness of a 21-gene Recurrence Score Assay in
Patients with Early Stage Breast Cancer
Malek Hannouf, University of Western Ontario,
University of Western Ontario, London, ON, Canada,
Malek.Bassam@schulich.uwo.ca, Bin Xie, Muriel Brackstone,
Greg Zaric
2 - Maintenance and Spare Part Inventory Control of Supercomputers
Xiaoyan Zhu, Assistant Professor, University of Tennessee, 408 East
xzhu5@utk.edu, Haitao Liao
We developed a Markov model to evaluate the cost effectiveness of a 21-gene
recurrence score assay versus current Canadian clinical guidelines in women with
early stage breast cancer. The model was parameterized using 5 and 10 year follow
up data from the Manitoba Cancer Registry and cost data from Manitoba Health.
To ensure the normal operation of a supercomputer, maintenance must be
performed effectively with the availability of spare parts to replace degraded or
failed units. This work provides a preliminary model that simultaneously
manipulates maintenance schedules and the number of spare parts to be held in
inventory to minimize the overall operating cost (downtime cost, and procurement
and holding costs for spare parts) while ensuring a high fill rate of spare parts.
■ WC45
3 - User Strategies for Super Computer Scheduling
Joe Wilck, The University of Tennessee - Knoxville, 411 East
Stadium, Knoxville, TN, United States of America, jwilck@utk.edu,
Jonathan Celso, Xueping Li, Mark Fahey
Radiation Therapy Optimization
Sponsored Session
We present strategies exhibited by users when using a super computer that has
priority scheduling. The schedule is prioritized to run jobs that utilize the most
nodes for the longest amount of time, and then backfills smaller jobs for the
remaining capacity. Due to maintenance schedules, the users know that the queue
must be cleared weekly.
Chair: Timothy Chan, Assistant Professor, University of Toronto, 5 King’s
College Road, Toronto, ON, M5S 3G8, Canada, tcychan@mie.utoronto.ca
1 - Quantifying the Trade-off Between Beam-on-time and Treatment
Plan Quality
Ehsan Salari, PhD Student, University of Florida, ISE Department,
P.O. Box 116595, Gainesville, FL, 32611-659, United States of
America, esalari@ufl.edu, Edwin Romeijn
4 - Supply Chain Management Models and Heuristics for Data
Cache Management
Zhe Zhang, Research Staff Member, Oak Ridge National Laboratory,
ORNL, 1 Bethel Valley Road, P.O. Box 2008 MS6008, Oak Ridge, TN,
37831-6008, United States of America, zhezhang@ornl.gov,
Xiaoyan Zhu, Rui Xu, Galen Shipman, Xiaosong Ma, Xueping Li
Beam-on-time is an important aspect of IMRT treatment efficiency, but its
optimization is traditionally postponed until the leaf sequencing phase of treatment
planning. However, there is a trade-off between treatment plan quality and beamon-time. The aim of this study is to incorporate the beam-on-time into a direct
aperture optimization model. We formulate a bi-criteria optimization model and
develop a solution method that efficiently obtains the entire set of Pareto-optimal
treatment plans.
For better application I/O performance, modern operating systems place certain data
blocks in faster storage devices based on future access predictions. In Computer
Science this method is named caching. While enhancing the system costeffectiveness, caching also creates challenges in data management, including data
placement and transfer. In this work we exploit the similarities between the caching
and supply chain management problems and apply SCM models and heuristics in
data cache management.
2 - A Beam Angle Optimization Approach for Intensity Modulated
Proton Therapy Treatment Planning
Gino Lim, Associate Professor PhD, University of Houston, E211,
Engineering Building 2, Houston, TX, 77204, United States of
America, ginolim@uh.edu, Wenhua Cao
We present an LP based local neighborhood search algorithm for solving the BAO
problem in IMPT treatment planning. Three prostate cancer cases at M. D. Anderson
were tested. Optimized angle sets demonstrated evident advantages comparing with
the lateral opposed angles currently used at M. D. Anderson. Furthermore, we
applied a worst case robust analysis that accounts for range uncertainties and setup
errors on the optimized angles in order to validate the robustness of plan quality.
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3 - An Inverse Optimization Approach to Determine Objective Function
Weights in Radiation Therapy
Taewoo Lee, PhD student, University of Toronto, 5 King’s College
Road, Toronto, ON, M5S 3G8, Canada, taewoo.lee@utoronto.ca,
Timothy Chan, Michael Sharpe, Tim Craig
Diversification in Projects
Invited Session
In a multi-objective optimization model for radiation therapy treatment planning,
the determination of weights for different organ-specific objective functions is based
on subjective beliefs and manual iterative loops. We present a linear inverse
optimization model that objectively and efficiently determines the weights using
historical treatment data from prostate cancer patients.
Chair: Karolina Glowacka, Assistant Professor, Stevens Institute of
Technology, Howe School of Technology Management, Hoboken, NJ,
07030, United States of America, kglowack@stevens.edu
1 - Impacts of Change Orders on Project Performance
Young Hoon Kwak, Associate Professor, The George Washington
University, Department of Decision Sciences, 2201 G Street, NW,
Suite 415, Washington, DC, 20052, United States of America,
kwak@gwu.edu, Kunhee Choi, Jane Park
4 - Dynamic Robust IMRT Optimization
Timothy Chan, Assistant Professor, University of Toronto,
5 King’s College Road, Toronto, ON, M5S 3G8, Canada,
tcychan@mie.utoronto.ca, Velibor Misic
Previous robust IMRT optimization studies used an uncertainty set to model data
uncertainty, solved a single treatment planning problem and delivered the solution
in all fractions. In this talk, we present a dynamic robust optimization methodology
where prior data observations are used to update the uncertainty set and guide
treatment re-optimization. We present results for a lung case demonstrating
simultaneous improvement in tumor coverage and lung sparing over non-dynamic
robust treatments.
Change orders are inevitable in infrastructure projects that often result in project
disruptions, disputes, and delays. We attempt to quantify the impacts of change
orders on project performance. Two different benchmarks, the original threshold
versus the amended threshold, of project cost, schedule, and other variables are
analyzed to measure the effect of change orders using 1372 infrastructure projects.
We also apply project portfolio analysis to determine the key effects on change
order.
2 - Analytic Contingency Setting: An Algorithm for
Estimating Contingencies
Homayoun Khamooshi, Assistant Professor, The George Washington
University, Decision Sciences,Funger Hall Room 408, 2115 G Street,
NW, Washington, DC, 20052, United States of America,
hkh@gwu.edu, Denis Cioffi
■ WC46
Game-Theoretic Applications in Healthcare II
Sponsored Session
To cover contingencies, usually a fixed percentage of a project budget is set aside.
Our model uses the binomial probability distribution to estimate the potential
number of risk realizations at a given confidence level, and ranked risk impacts are
added over this number of risks, yielding the required contingency funds to provide
coverage of the accepted risks. The budget found with this method compares
extremely well with one ascertained from a numerical simulation of the risk
occurrences.
Chair: Murat Kurt, PhD Student, University of Pittsburgh, Department of
Pittsburgh, PA, 15217, United States of America, muk7@pitt.edu
Co-Chair: Reza Yaesoubi, Post-Doctoral Research Fellow, Harvard Medical
School, 641 Huntingtone Ave., Boston, MA, 02115, United States of
America, reza.yaesoubi@gmail.com
1 - Influenza Vaccine Supply Chain Coordination with Certain Delivery
and Asymmetric Information
Javad Nasiry, HKUST, Clear Water Bay, Kowloon, Hong Kong - PRC,
Javad.NASIRY@insead.edu, Stephen E. Chick, Sameer Hasija
3 - Integrating Innovation Projects and Lean Six Sigma Projects in the
Organizational Portfolio
Frank T. Anbari, Clinical Professor, Drexel University, Goodwin
College of Professional Studies, 3001 Market St., Suite 100,
Philadelphia, PA, 19104, United States of America,
anbari@drexel.edu
We develop a model to investigate the effects of information asymmetry between a
manufacturer and a single buyer on flu vaccine supply chain coordination. We
design an optimal menu of output-based screening contracts and develop a simple
alternative menu that can achieve screening with no loss of efficiency under some
conditions. The policy implications of the model are further discussed.
There are two concurrent, major waves affecting management thinking currently:
project management/ innovation and Lean Six Sigma/ process improvement.
Management researchers in each of these two important areas are seldom aware of
the progress achieved in the other area. We aim to provide a clear vision of the
integration of the project management office (PMO)/ innovation and Lean Six
Sigma operations to enhance the organization’s performance through continual
improvement of its total system.
2 - Imaging Room and Beyond: The Underlying Economics Behind
Physicians’ Test-Ordering Behavior
Tinglong Dai, PhD Student, Carnegie Mellon University, Tepper
School of Business, Pittsburgh, PA, 15213, United States of America,
dai@cmu.edu, Sridhar Tayur, Mustafa Akan
4 - OptForceTM: A New Approach to Strategic Workforce Planning
Jay April, OptTek Systems, Inc., 2241 17th Street, Boulder, CO,
80302, april@opttek.com
Excessive diagnostic tests have long been viewed as one major aspect of health care
inefficiency and are often attributed to the fee-for-service payment model. In this
study we investigate the underlying operational and economic drives behind
physicians’ test-prescribing behavior in the outpatient setting, motivated by a
collaborative study with a major outpatient clinic. Our work also provides insights
into the effects of the increasingly popular “comparison shopping” of health
services.
Companies annually invest billions of dollars in programs to pursue objectives such
as improving workforce productivity, customer satisfaction, customer contracting
requirements and legal settlements. OptForceTM provides significant benefits in
these settings, by evaluating and selecting portfolios of proposed investments in
programs to generate new decision alternatives that offer improved returns.
3 - Stochastic Dynamic Allocation of Deceased-donor Kidneys
M Gisela Bardossy, University of Maryland, R.H.Smith School of
Business, and Institute for Systems Research, College Park, MD,
United States of America, bardossy@umd.edu, Inbal Yahav
Deceased-donor kidneys are currently allocated to candidates through a priority
point system that combines waiting times and human tissue matches. In this paper
we evaluate a stochastic dynamic programming approach in search of rules of
allocation that maximize a multicriteria objective to balance efficiency with equity.
We test our approach on the current candidates’ kidney waiting list and find
promising results.
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Tutorial: The Role and Challenges for Optimization in
Competitive Electricity Markets
Information Systems II
Cluster: Tutorials
Invited Session
Chair: Narges Kasiri, Assistant Professor, SUNY Oneonta, 2004 E
Matthews, stillwater, OK, 74075, United States of America,
kasiri@okstate.edu
1 - Differential Privacy in the Context of Masking Numerical Data
Krish Muralidhar, Professor, University of Kentucky, School of
Management, Lexington, KY, 40506-0034, United States of America,
krishm@uky.edu, Rathin Sarathy
Contributed Session
Chair: Shmuel Oren, Professor, University of California-Berkeley, IEOR
Department, 4135 Etcheverry Hall, Berkeley, CA, 94720,
United States of America, oren@ieor.berkeley.edu
1 - The Role and Challenges for Optimization in Competitive
Electricity Markets
Shmuel Oren, Professor, University of California-Berkeley, IEOR
Department, 4135 Etcheverry Hall, Berkeley, CA, 94720,
United States of America, oren@ieor.berkeley.edu
Recently, researchers at Microsoft have proposed a new privacy standard called
Differential Privacy. In this study, we evaluate the efficacy of using differential
privacy when numerical confidential data is masked.
2 - Analysis of Spamming Behavior at Different Aggregation Levels and
Implications for IT Security
Serpil Sayin, Dr., Koç University, Rumeli Feneri Yolu, Sariyer,
Istanbul, 34450, Turkey, ssayin@ku.edu.tr, John Quarterman,
Manoj Parameswaran, Andrew Whinston
This tutorial will describe key challenges in designing and operating competitive
electricity markets. It will review the basic components of electricity markets and
alternative structural approaches adopted in different systems. We will discuss the
underlying optimization problems being solved in scheduling, operating and
simulating electricity markets. New computational challenges and research activities
in this area will also be reviewed.
Using e-mail spam data from different blocklist sources, we analyze the observed
spamming behavior at the single IP and Autonomous System (AS) levels. Our single
IP level study reveals the variability in the spamming tactics employed by different
botnets. Our AS level analysis indicates that the distribution of spam contribution is
highly skewed across organizations. We discuss the role of a reputation system in
alternative incentive mechanisms to address IT security concerns.
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Intellectual Property Issues in Technology
3 - When Should Software Firms Commercialize New Products via
Freemium Business Models
Marius Florin Niculescu, George Institute of Technology, College of
Management, 800 West Peachtree Street NW, Atlanta, GA, 30308,
United States of America, marius.niculescu@mgt.gatech.edu,
D. J. Wu
Sponsored Session
Chair: Eric Walden, Wetherbe Professor of ISQS, Rawls College of
Business, Box 42101, Lubbock, TX, 79409, United States of America,
eric.walden@ttu.edu
1 - On the Downloading vs. Uploading of Unauthorized Copies of
Intellectual Property
Jared Hansen, Assistant Professor, University of North Carolina at
Charlotte, 9201 University City Boulevard, Charlotte, NC, 28223,
United States of America, Jared.Hansen@uncc.edu, Eric Walden
Freemium approach, whereby a firm gives away for free a certain level or type of
consumption while making money on premium consumption, is spreading fast in
the software industry. We advance a multiperiod framework with network
externalities in order to describe several freemium business models. We solve firm’s
optimal pricing strategy under each model, derive conditions when freemium
models are superior to conventional for-fee and seeding models, and discuss
managerial and policy implications.
This research examines differences in ethical and legal perceptions regarding the
downloading versus uploading of music files through unauthorized file sharing. Two
explanations are tested (to explain willingness to participate): (1) restrictedness of
use, (2) word of mouth (WOM). Survey results indicate different effects for
uploading and downloading behavior. In short, consumers use different heuristics in
deciding whether to participate in downloading versus uploading.
4 - Valuing RFID Investment in the Retail Sector: A Real Options Model
Narges Kasiri, Assistant professor, SUNY Oneonta, 2004 E Matthews,
stillwater, OK, 74075, United States of America, kasiri@okstate.edu,
Ramesh Sharda
The investment in Item-level RFID in the retail sector similar to any other IT
investments is associated with high uncertainties in its potential benefits and costs.
A real options approach is appropriate to analyze the cost and benefits of the
investment problem. We apply a system dynamics simulation technique to generate
the parameters of the real options model and discuss various options and scenarios
retailers have in implementing item-level RFID in retail operations management.
2 - Digital Piracy: Trends in the Perception of Consequences
Abbe Forman, Assistant Professor Teaching/Instruction, Temple
University, 435 Alter Hall, 1805 N. Broad St, Philadelphia, PA,
19122, United States of America, abbe.forman@temple.edu
Digital piracy continues to be an alarming problem. Attempts to slow or stop the
theft of intellectual property have been nearly futile. Many people do not believe
that digital piracy is a crime or that they will “get caught”. This study represents an
analysis of the literature regarding perceived consequences of digital piracy between
2001 and 2009. Additionally, the results of an open ended questionnaire asking
specifically about perceived consequences will be presented.
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3 - Designing Content Licensing Arrangements for Boundary
Management in Hybrid Business Models
Karl Lang, Professor of Information Systems, Baruch College,
Zicklin School of Business, City University of New York,
Karl.Lang@baruch.cuny.edu, Sirkka Jarvenpaa
Analysis at US Army Aviation and Missile
Command (AMCOM)
Using data from economic experiments and case studies from the music industry we
find that boundary management, i.e. managing the organizational tension that the
overlapping of commercial and sharing economies create, is a key success/failure
factor for hybrid business models that combine elements of the private investment
and collective action models. We argue that licensing design specifying the content
access and reuse rights for consumers is a critical for effective boundary
management.
Chair: Wayne Bruno, Director, Command Analysis, U.S. Army Aviation &
Missile Command, BLDG 5308, Restone Arsenal, Al, 35898,
United States of America, wayne.bruno@us.army.mil
1 - A Method for Determining the Mismatch Between Supply and
Demand in the Army Supply Chain
David Berkowitz, Professor of Marketing, University of Alabama Huntsville, 301 Sparkman Drive, College of Business Administration,
Huntsville, AL, 35899, United States of America, berkowd@uah.edu,
Lucas Neidert, Al Wilhite, Fan Tseng
Sponsored Session
4 - Running in the Pack vs. Running Alone: When Does It Make Sense
to Jointly Develop a Technology?
Nitin Aggarwal, Assistant Professor, San Jose State University,
1 Washington Square, San Jose, CA, 95192-0244,
United States of America, aggarwal_n@cob.sjsu.edu
Our paper develops a method for determining the mismatch between inventory
control point supply and the field level demand for a Class IX item. We identify the
characteristics of items that are likely to be in short supply. We determine the
probability structure for supply. Then we run a regression based model to help
predict demand. Finally we match the results to project a supply on hand at the end
of a period.
We collect data from 436 experts involved in technology development to confirm
that technology is made up of bundles of intellectual property, mostly owned by
different entities. The data shows that there are significant transaction costs - search,
coordination, and opportunism - involved in assembling the bundle. Initially, these
costs are lower for hierarchies, but they gradually increase with complexity, nonsubstitutability, and IP distribution patterns, thereby making networks economical.
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2 - Demonstrating the Business Case for Condition-Based
Maintenance (CBM) in Army Aviation
Josh Kennedy, Chief, Ops Analysis Branch, Command Analysis
Directorate, US Army Aviation & Missile Command, Bldg 5308,
Redstone Arsenal, AL, 35898, United States of America,
josh-kennedy@us.army.mil
WC53
5 - Transient Analysis of the Border Crossing Process using Congestion
Based Policies
Hiram Moya, PhD Candidate, Texas A&M University,
2807 Henry Ct., College Station, TX, 77845,
United States of America, Hiram@tamu.edu
Trade is the U.S. depends on an efficient flow of inspected containers in and out of
the border ports of entry (POE), while focusing on security, and being cost effective.
This research focuses on all commercial traffic at a southern border POE, where
there is a non-steady state, terminating system. Using transient analysis, we present
analytical and experimental results of congestion based policies with a fixed number
of servers, by implementing a primary inspection station service switch.
The Army’s Aviation & Missile Command is pursuing a large-scale CBM program for
its helicopter fleet. DoD has directed CBM as a reliability and sustainability driver in
life cycle systems management. The objectives for AMCOM’s CBM program are:
decrease Soldier maintenance burden, increase availability, enhance safety, and
reduce costs. However, the investment required for a CBM program is substantial.
This presentation outlines how AMCOM made a clear business case for this
investment.
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3 - Application of Cost-Benefit Analysis (CBA) to Respond to Army
Aviation Maintenance Issues
Tina Theiss, Operations Research Analyst, Command Analysis
Directorate, US Army Aviation & Missile Command, Bldg 5308,
Redstone Arsenal, AL, 35898, United States of America,
tina.theiss@us.army.mil
Operations/Marketing Interface II
Contributed Session
Currently, there is no cyclic Army Aviation sustainment program to mitigate risk
associated with the long term effects of airframe aging and use. At the same time,
the Army has initiated a thorough CBA process to accompany unfunded
requirements, the net result of which should be a strong value proposition stating
that the benefits of a new requirement more than justify the costs. This presentation
discusses how we applied the CBA process to respond to shortfalls with helicopter
maintenance.
Chair: Kunpeng Li, Sam Houston State University, Avenue I, Huntsville,
TX, United States of America, kli@shsu.edu
1 - The Effect of Traffic on Retail Store Conversion Rate and Sales
Olga Perdikaki, Assistant Professor, Texas A&M, Mays Business
School, College Station, 77843-4217, United States of America,
operdikaki@tamu.edu, Jayashankar Swaminathan,
Saravanan Kesavan
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In this paper, we use proprietary data pertaining to a retailer to study the
relationship between traffic and store sales performance, measured as the number of
transactions and sales volume. We find that store sales performance exhibits
diminishing returns to scale with respect to store traffic and increases in traffic
variabilities are associated with declines in store sales performance. Finally, we find
that store labor moderates the impact of traffic on store sales performance.
Homeland Security
2 - Product Line Decision with Incomplete Information
Michael Lim, Asst Professor, University of Illinois, 350 Wohlers Hall,
1206 S. 6th Street, Champaign, 61820, United States of America,
mlim@illinois.edu
Contributed Session
Chair: Hiram Moya, PhD Candidate, Texas A&M University,
2807 Henry Ct., College Station, TX, 77845, United States of America,
Hiram@tamu.edu
1 - Infrastructure Security via Game Theory
Zhe Duan, Rutgers University, 900 Davidson Road, Apt. 94,
Piscataway, NJ, 08854, United States of America,
duanzhe@gmail.com, Melike Baykal-Gursoy
We study manufacturer’s product line length decision under information asymmetry
where retailer has a private information regarding local consumers’ preference. We
use mechanism design to construct a contract that elicits retailer’s information rent.
Our analysis identifies the condition in which the manufacturer have more (or less)
incentive to extend the product line compared to full information case. We will also
discuss some insights and policy implications from the model.
Recent attacks in Mumbai, Russia, and the attempted attack in New York city have
forced governments to devote significant time and resources to secure
infrastructures. In this paper, we study how to secure infrastructures via game
theory. The uncertainty of the timing and the location of an attack is alleviated by
considering the occupancy level of each location. Zero-sum and non-zero sum
games are solved and equilibrium policies are obtained.
3 - Return Policies and Informational Tools in Experience
Goods Markets
Eylem Koca, University of Maryland, College Park, Smith School of
Business, VMH 3330, College Park, MD, 20740,
United States of America, ekoca@umd.edu, Gilvan Souza
2 - Protecting Electric Power Systems From Terrorist Attacks
Vanlapha Santithammarak, PhD Student, Texas Tech University,
2619 19th St. Apt 10, Lubbock, 79410, United States of America,
vanlapha.santithammarak@ttu.edu, Milton Smith
We investigate the role of return policies and informational tools provided by the
seller in consumer purchasing behavior and on the overall market outcome. We
build a model of consumer learning and analyze a seller’s decision process in a twoperiod setting. We attain significant analytical findings with no distributional
assumptions, and fully study the joint optimization problem under uniform
valuations. Finally, we study competition in a duopoly setting, and look at some
extensions.
Terrorist attacks designed to weaken the economy are increasing concern after 9/11.
Electrical power systems should be regarded as likely targets of terrorists due to the
most effects of economic activities. The objective of this study is to investigate the
methods for protecting from physical attacks and reducing vulnerability in power
system networks.
4 - Shelf Space Competition Between Store and National Brands
Shu-Jung Sunny Yang, Lecturer in Management, The University of
Melbourne, Level 10, 198 Berkeley Street, Melbourne, 3010,
Australia, sunnyy@unimelb.edu.au, Chia-wei Kuo, Pei-Ju Lu
3 - Safe Path Optimization with Local Protection Required
Ruben Dario Yie Pinedo, University at Buffalo (SUNY), Department
of Industrial & Systems Engg, 308 Bell Hall, Buffalo, NY, 14260,
United States of America, rubenyie@buffalo.edu, Rajan Batta,
Moises Sudit
Shelf space allocation is one of the retailer’s most challenging operational decisions.
We propose a game-theoretic model in which one retailer, acting as a leader by
deciding the total shelf space available and selling both national and store brands,
maximizes her category profit, and one national-brand manufacturer, acting as a
follower, maximizes his own profit. Our analysis suggests that the allocation of the
shelf space depends on two thresholds of total shelf space for both brands.
The edges in a network can be exposed to certain events that compromise the safety
of the vehicle. To reduce the likelihood of an event protection could be used. This
talk will discuss the problem of routing several vehicles from multiple origins to
multiple destinations. The network contains zones in which local protection is
required. Local escorts are not allowed to leave their jurisdiction zones. The main
objective is to minimize the total treat level to which the vehicles are exposed.
5 - Optimal Price Reduction Strategy in Product Sales
Kunpeng Li, Sam Houston State University, Avenue I, Huntsville, TX,
United States of America, kli@shsu.edu, Chongqi Wu
4 - A Risk Based Sensor Allocation Problem
Amir Ghafoori, PhD Student, Rutgers University, Department of
Industrial and Systems Eng, 96 Frelinghuysen Road, Piscataway, NJ,
08854, United States of America, ghafoori@eden.rutgers.edu
Consumers with high valuation are willing to pay a higher price than those with
low valuation. Therefore, firms should make sure that consumers with high
valuation buy first. Later on, firms reduce the product price and sell to consumers
with low valuation. Under such a setting, our paper investigates many important
questions in the decisions of product design and introduction.
We develop a risk based model for underwater sensor allocation to detect divers.
The model investigates various aspects of sensor placement problems for underwater
application and attempts to put sensors in the set of candidate grid points. Each
sensor type brings its specifications to the model and poses a level of complexity.
Finally an optimal scheme of sensor positioning is proposed in order to minimize
the average total risk in the field.
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Innovation Management for Sustainability
Innovation and the Economy
Sponsored Session
Sponsored Session
Chair: Hsueh-Ming Wang, Associate Professor, University of Alaska
Anchorage, ESM Department 3211 Providence Dr., Anchorage, AK,
99508, United States of America, afhsw1@uaa.alaska.edu
1 - Curriculum Development for the Innovation Management Program
for Sustainability
Seong Dae Kim, Assistant Professor, University of Alaska Anchorage,
PM Department at University Center, Room 155, 3901 Old Seward
Highway, Anchorage, AK, 99503, United States of America,
afsdk1@uaa.alaska.edu, Hsueh-Ming Wang
Chair: Erica Fuchs, PhD, Carnegie Mellon University, 5000 Forbes
Avenue, Baker Hall 129, Pittsburgh, PA, 15217, United States of America,
erhf@andrew.cmu.edu
1 - Patents, Materials Transfer Agreements (MTAs), and the Flow of
Scientific Knowledge
David Mowery, Professor, University of California Berkeley, HAAS,
mowery@haas.berkeley.edu, Neil Thompson, Arvids Ziedonis
How does university involvement in academic patenting affect academic science?
This paper extends the work of Murray and Stern (2007) to cover a broader sample
of published scientific papers in the biomedical and other disciplines, and examines
the effects of both patenting and material transfer agreements (MTAs) on citations
to scientific papers.
The curriculum is focusing on the sustainability through the innovation of quality of
life. This program will help students for building industry careers as system
designers, architects, project managers, developers, and entrepreneurs and providing
students with broad understanding of green engineering, energy saving lighting, and
innovation of quality of life as well as to stimulating the development and
application of energy efficient lighting, green technologies with quality innovation.
2 - Economic Downturns, Inventor Careers, and Technology
Trajectories in the U.S
Wunmi Akinsanmi, PhD Student, Carnegie Mellon University,
5000 Forbes Avenue, Baker Hall 129, Pittsburgh, PA, 15217,
United States of America, eyidearie@gmail.com, Erica Fuchs
2 - The Critical Factors for Decision-making of the Technology
Policies of the Industrialized Countries for Municipal Solid
Waste Management
Leslie Simmons, PhD Student, University of Alaska, 3211 Providence
Dr, Anchorage, AK, 99508, United States of America,
aflfs@uaa.alaska.edu, Hsueh-Ming Wang
This research explores the relationship between the telecommunications bubble
burst and the quantity, direction and locus of U.S. innovation. We focus on
optoelectronics, a general purpose technology with applications in energy,
biomedical, telecommunications, computing and military. Leveraging USPTO patents
and inventor CVs, we analyze how inventors’ pre-bubble productivity, mobility,
social capital and degree of specialization influence these same post-bubble and
thereby the national trend.
In the United States of America, landfill disposal is a major method to handle
municipal solid waste. It may generate pollutants and carbon emissions in the
environment. Some industrialized countries, such as Germany, Denmark, and
Japan, are using technologies to reduce, reuse, recycle, or combust to limit amounts
of land disposed municipal solid waste. Technology policies from governments
generate different outcomes of solid waste management. Many factors may affect
policy-making process. This research evaluates critical factors that impact technology
policies by surveying and comparing results in industrialized countries. Critical
impact factors for decision-making priorities differ between the USA and other
industrialized countries. These different technology policies may affect
environmental protection and carbon emissions in the future.
3 - Intellectual Property, Prior Knowledge & New Firm Survival
Sonali Shah, Buerk Fellow and Assistant Professor, University of
Washington, Box 353200, Seattle, WA, 98195, United States of
America, skshah@u.washington.edu, Sheryl Winston Smith
We examine the joint effects of founders’ prior knowledge and intellectual property
protection on the survival of young firms. We examine three different sources of a
founder’s prior knowledge: prior industry experience, prior entrepreneurial
experience, and prior entrepreneurial experience in the same industry. Taken
together, our findings show the importance of patents as strategic, as well as
appropriability, tools and are in-line with evolutionary economic theory.
3 - Cognitive Oriented Integration for Innovation Management
Hsueh-Ming Wang, Associate Professor, University of Alaska
Anchorage, ESM Department 3211 Providence Dr., Anchorage, AK,
99508, United States of America, afhsw1@uaa.alaska.edu,
Muchiu Chang
■ WC56
The acceptance of a new product depends on the market needs of the innovation
and service compliance through the product life. We develop an innovation
management process by cognitive based consumer behaviors integration. It includes:
new ideas to lead the customer needs, adopting new technology in design, patent
mapping market anaylsis, and life cycle management. Modeling simulation is a
robust solution to virtually validate and verify the life cycle behaviors of various
design concepts.
C - Room 1, Level 1
Simulation and Optimization I
Contributed Session
Chair: Honggang Wang, Stanford University, Department of Energy
Resources Engi, Stanford, CA, 94305, United States of America,
honggang@stanford.edu
1 - Stochastic Dominance Based Ranking and Selection in Simulation
Demet Batur, University of Nebraska- Lincoln, 175 Nebraska Hall,
Lincoln, NE, United States of America, dbatur2@unl.edu,
Fred Choobineh
4 - Agility Management for the Project Sustainability
Peter Lang, Graduate Student, University of Alaska Anchorage, ESM
Department, 3211 Providence Dr., Anchorage, AK, 99508, United
States of America, peter@alaskadatatech.com, Hsueh-Ming Wang
The projectized organization surrounding culturalvalues addresses concerns of
balancing versus optimizing various value propositioning factors. Information
Technology for project portfolios selection processes may profit by looking across a
variety of fields ranging from project management to the cognitive sciences to
increase project agility. The solutions may obtain by meta-modeling balancing,
aligning, and integrating a proposed adaptive risk management approach.
We present a ranking and selection procedure where simulated systems are
compared based on the stochastic dominance relationship of a performance metric
of interest. The system which stochastically dominates all other systems is deemed
as the best system. If there is not a unique best system, but a number of systems
with crossing distribution functions, then the proposed procedure selects a set of
nondominated systems with a probability of correct selection guarantee.
2 - Modeling the Relative Efficiency of Job Assignment in Differing
Social Structures
Paul Kerl, Georgia Institute of Technology, 765 Ferst Drive, NW,
Atlanta, GA, 30332, United States of America, paul.kerl@gatech.edu,
Joel Sokol
In the recent and distant past, people have found their job in many different ways,
from inherited positions to national testing and matching. We use stylized
assignment models to examine several social structures and measure the relative
benefit of structural characteristics. These characteristics include job inheritance,
split social structures, heuristic selection versus optimal selection of jobs, job
mobility, and the marginal value of information about person-job matching.
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3 - Use of Retrospective Optimization for Placement of Oil Wells
Under Uncertainty
Honggang Wang, Stanford University, Department of Energy
Resources Engi, Stanford, CA, 94305, United States of America,
honggang@stanford.edu, David Echeverri Ciaurri, Louis Durlofsky
C - Room 3, Level 1
Financial Engineering I
Contributed Session
Determining well locations in oil reservoirs under geological uncertainty remains a
challenging problem in field development. We simulate (with a reservoir simulator)
multiple model realizations to estimate the expected field performance for a certain
well placement. The presented RO framework generates a sequence of sample-path
problems with increasing sample sizes. The numerical results show that the RO
algorithm finds a solution yielding a 70% increase in the NPV for the problem
considered.
Chair: Arun Chockalingam, Visiting Assistant Professor, Purdue
University, 315 N. Grant Street, West Lafayette, IN, 47907,
United States of America, achockal@purdue.edu
1 - Margining Option Portfolios by Offsets with Two, Three and
Four Legs
Dmytro Matsypura, Dr, The University of Sydney,
Merewether Building H04, Sydney, 2006, Australia,
dmytro.matsypura@sydney.edu.au, Vadim Timkovsky
4 - Water Quality Monitoring Network Design using Optimization
via Simulation
Chuljin Park, PhDStudent, Georgia Technology of Institute, 765 Ferst
Dr NE, Main Building #124, Atlanta, GA, 30332, United States of
America, cpark41@mail.gatech.edu, Seong-Hee Kim, Ilker Telci,
Mustafa Aral
As shown in [Rudd and Schroeder, 1982], the problem of margining option portfolios where option spreads with two legs are used for offsetting can be solved in
polynomial time by network flow algorithms. In this paper we extend this result to
the case where option spreads with three and four legs can also be used for
offsetting and propose a general method of margining option portfolios.
The problem of designing a water quality monitoring network for river systems is to
find the optimal location of a finite number of monitoring devices that minimizes
the expected detection time of a contaminant spill event with good detection
reliability. We set a stochastic constraint on detection reliability and solve the
monitoring design problem using optimization via simulation.
2 - Cross Validation and Various Techniques in Utilizing Financial Time
Series Data for Model Validation
Wing-Ho Choi, Gradient Analytics, 14614 North Kierland Boulevard,
Scottsdale, AZ, 85254, United States of America, wc447@cornell.edu,
Derek Koh
When modeling financial data using insamples and outsamples, one has to account
for the information overlap of return information which can create an optimistic
bias on results. This is typically done by imposing a blackout period between in and
out samples. The period is dependant on the return horizon where a long horizon
results in a larger blackout period. This paper modifies the cross-validation
technique and explores methods that optimizes the use of data available for
financial modeling.
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C - Room 2, Level 1
Risk Analysis
Contributed Session
Chair: John Chachere, Senior Computer Scientist, Stinger Ghaffarian
Technologies, 1060 Arbor Road, Menlo Park, CA, 94025,
United States of America, john.m.chachere@nasa.gov
1 - Why Do Groups Cooperate More Than Individuals to Reduce Risks?
Min Gong, Columbia University, 1190 Amsterdam Ave,
406 Schermerhorn Hall - MC 5501, New York, NY, 10027,
United States of America, mingong@gmail.com, Jonathan Baron,
Howard Kunreuther
3 - New Estimation Techniques for Fractional Brownian Motion with
Applications to Finance
Daniel Scansaroli, PhD Candidate, Lehigh University, 200 West
Packer Ave., Industrial Engineering Department, Bethlehem, PA,
18015, United States of America, djse@lehigh.edu, Robert H. Storer,
Vladimir Dobric
We explore financial applications of fractional Brownian motion and present two
new methods of estimating the parameters of this process based on ergodic theory.
We evince that in a fractional Brownian market, the typical assumption of
independent increments results in an underestimation of market risk and a term
structure of volatility. We conclude by applying our new technique to the equity
market to show the behavior of the Hurst index that over the last 35 years.
We find that groups are less cooperative than individuals in a prisoner’s dilemma,
but are more cooperative than individuals in a stochastic version of the game.Three
processes are tested: risk concern, cooperation expectation, and social pressure. Data
shows that guilt aversion and blame avoidance cause groups to be more risk
concerned than individuals, which drives groups to cooperate to reduce risks.
Groups also have higher cooperation expectations for their counterpart than
individuals have.
4 - Moving-boundary Approaches for American Security Valuation
Arun Chockalingam, Visiting Assistant Professor, Purdue University,
315 N. Grant Street, West Lafayette, IN, 47907, United States of
America, achockal@purdue.edu, Kumar Muthuraman
2 - Decision Support for Inland Waterways Emergency Response
Leily Farrokhvar, University of Arkansas, 4207 Bell Engineering, W
Dickson Street, Fayetteville, AR, 72701, United States of America,
lfarrokh@uark.edu, Heather Nachtmann, Ed Pohl
Pricing American options gives rise to a free-boundary problem in PDEs (PIDEs if
the asset price process is discontinuous). We present a computational scheme that
solves for the option price and optimal-exercise policy by converting the freeboundary problem into a sequence of fixed-boundary problems. This scheme is
general enough to handle a variety of market models. We also discuss error bounds
for options priced with sub-optimal exercise policies and the implications of these
bounds.
Emergency planning involving transportation resources requires thorough
contingency planning in case of route destruction due to natural or man-made
events. Inland waterways can provide emergency transportation to a large area of
the United States. We explore the potential for communities to benefit from inland
waterway emergency response through the development of a decision support
framework to support an inland waterway-based emergency response system.
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3 - Quantitative Method for Analyzing Engineering Defect
Risks in Projects
Technologies, 1060 Arbor Road, Menlo Park, CA, 94025,
United States of America, john.m.chachere@nasa.gov
Operations Management VII
Contributed Session
Engineering defects often cause complex systems to fail. I provide a quantitative
model of defects linking causes in an upstream development project to effects on
downstream operations failure risks. The Model integrates: a simulation of the
development project, a probabilistic analysis of operations failure risks, and a
rational model of project decisions (e.g., organizational structure) and product
decisions (e.g., subsystem redundancies). I evaluate an example project.
Chair: Jieling Han, PhD Student, Department of ISOM / University of
Washington, Department of ISOM, Box 353200, University of
Washington, Seattle, WA, 98115, United States of America, hanjl@uw.edu
1 - Optimal Pallet Loading Problem with Complex Stacking Constraints
Amit Garg, Senior Logistics Engineer, Penske Logistics,
amit.garg@penske.com, Vishwa Ram, Prasad Natarajan,
Kevin Troyer, Mitch Plesha
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Optimal Pallet Loading Problem is an important problem in the logistics industry.
We investigate a particular problem for a food manufacturer where several
categories of items need to be placed on the least number of pallets. Each item
category primarily differs with other categories in the stacking constraints and
product charactrestics. There are also specific business rules that dicatate how any
two or more item categories can be placed on the same pallet. Current solution
techniques and available commerical software solutions are unable to solve this
problem because of the pecularities of the business rules and packing preferences in
near real time for several thousand orders every day. Therefore, we implement a
heuristc solution that takes various stacking rules and packing preferences and
minimizes the number of pallets required for each order.
WC62
2 - Profit- vs. Cost-orientation in the Newsvendor Problem: Insights
From a Behavioral Study
Sebastian Schiffels, Technische Universitaet Muenchen,
TUM School of Management, Muenchen, 80333, Germany,
sebastian.schiffels@wi.tum.de, Jens Brunner, Rainer Kolisch,
Andreas Fuegener
4 - Comparing Organizational Forms in the Trucking Industry
Johan Lundin, PhD Student, Lund University, Box 118, Lund,
22100, Sweden, johan.lundin@tlog.lth.se, Fredrik Eng Larsson
Studies on organizational forms pertaining to efficiency show that pricing and
deciding upon the right level of output can vary between forms (Porter and Scully,
1987). Never before has the trucking been studied from this perspective, which is
why we focus on exploring the truck investment decision based on economic
efficiency. The methodology draw on industrial organization and game theory using
a two-stage supply chain model under deterministic demand expressed as a Cournot
competition model.
Our research investigates differences in the behavior of individuals in a profit- vs. a
cost- orientated newsvendor problem. Our hypothesis is that individuals order more
in the cost orientated than in the profit orientated newsvendor setting. Previous
studies (e.g. Schweitzer and Cachon 2000) show that individuals deviate from the
expected optimal decision in the newsvendor game. In fact, they tend to order less
(more) than the expected profit maximizing order quantity if per unit profit margin
is high (low). To test our hypothesis we set up a laboratory study which takes into
account the profit or the cost perspective and three critical ratios. Our results
confirm our hypothesis as well as the findings of previous studies. In each of the
defined critical ratios the average order quantity in the cost orientated newsvendor
game is significantly higher than in the profit orientated problem. The results imply
that people underlie systematical different biases when facing profit and cost
orientated situations.
5 - Assessment of the Impact of Undesirable Outputs on the
Productivity of US Motor Carriers
Rodrigo Britto, University of Maryland, 3909 Stoconga Drive,
Betlsville, MD, 20705, United States of America,
rbritto@rhsmith.umd.edu, Thomas Corsi
This research evaluates the impact of undesirable outputs (i.e; crashes and fatalities)
on the productivity of motor carriers during the years 1999-2003. The nonparametric direction output distance function and an additive DEA model are used
to model both desirable and undesirable outputs. Tobit regression is applied in a
second stage to analyze the drivers of efficiency.
3 - Dynamic Scheduling Policy in a Make-to-stock System with Two
Demand Classes of Different Variability
Jieling Han, PhD Student, Department of ISOM / University of
Washington, Department of ISOM, Box 353200, University of
Washington, Seattle, WA, 98115, United States of America,
hanjl@uw.edu, Apurva Jain
■ WC63
We consider the dynamic scheduling policy in a make-to-stock queue with a single
server, exponential processing times, standard holding and backorder cost rates, and
two demand classes that differ in their variability. We partially characterize the
optimal scheduling policy and propose heuristics. We then analyze the case where
the centralized server has information about the arrival process of the more variable
demand class and show the value of this information.
Decision Analysis V
Contributed Session
Chair: Onur Bakir, Visiting Assistant Professor, Bilkent University, Bilkent
Universitesi, Endüstri Mühendisligi Bˆlümü, Ankara, 06800, Turkey,
nonur@bilkent.edu.tr
1 - Deciding on the Decision Frame (The Most Important Decision of
the Analysis)
Roberto Ley-Borras, Director, Consultoria en Decisiones, Oriente 13
A No. 1122, Orizaba, Ver., Mexico, rley@decidir.org
■ WC62
Identifying the right decision frame is generally regarded as a critical part of a
decision analysis, but there are few guidelines on how to achieve that. This talk
presents a simple algorithm and some advice on generating decision frames and
selecting the one that is best for the decision-maker’s current priorities and
circumstances. Our proposed approach is considering the selection of the decision
frame a decision situation by itself and using DA tools to gain clarity on the best
frame.
Transportation, Operations
Contributed Session
Chair: Rodrigo Britto, University of Maryland, 3909 Stoconga Drive,
Betlsville MD 20705, United States of America, rbritto@rhsmith.umd.edu
1 - Mapping Transportation Waste
Bernardo Villarreal, Professor, Universidad de Monterrey, I. Morones
Prieto 4500 Pte, San Pedro Garza Garcia, NL, 62638, Mexico,
bvillarreal@udem.edu.mx
2 - Modified Repertory Grid Approach to Developing Criteria for MCDM
Eric Johnson, Decision Strategies, Inc., 10260 Westheimer Road,
Suite 250, Houston, TX, 77079, United States of America,
ERJohnson@DecisionStrategies.com
Value stream mapping was developed originally to identify and eliminate waste in
the manufacturing area. This is extended to design improvement programs oriented
to eliminate waste for transport operations. The definition of several types of waste
specific to transportation with the goal of improving efficiency as the relevant
performance measure is suggested. Application to real examples is provided.
Multi-criterion decision making has been widely used for decisions where
stakeholders do not agree on a single overriding objective. Assessment of criterion
weights and scores is well understood. But all too often the criteria are too vague to
be properly judged, or are understood differently by different judges, leading to
results that aren’t compelling or don’t even make sense. This talk describes a novel
protocol for eliciting objectives, and illustrates its benefit in a disguised case.
2 - An Integrated Model for Resource Allocation and Scheduling in a
Transshipment Container Terminal
Nabil Nehme, PhD Candidate, American University of Beirut, P.O.
Box 11-0236, Riad El Solh, Beirut 11, Beirut, Lebanon,
nhn02@aub.edu.lb, Isam Kaysi, Farah Mneimneh, Bacel Maddah
3 - A Multiple Criteria Sorting Method Based on Support
Vector Machines
Esra Karasakal, Industrial Engineering Department, Middle East
Technical University, Ankara, 06530, Turkey, esra@ie.metu.edu.tr,
Asli Duman
This paper considers the coordination between quay and yard sides in a
transshipment process at a container terminal. A model is developed to minimize
the number of cranes used and to determine the optimal schedule for unloading
containers for a vessel. Several insights are drawn illustrating the importance of
coordination.
In this study we develop a method based on Support Vector Machines (SVM) for
multiple criteria sorting problems. We modify SVM models to handle preference
ordering of classes. We compare the proposed method with SVM models on several
example problems.
3 - A New Packing Heuristic Based Approach for the VRP with Threedimensional Loading Constraints
Yi Tao, PhD Candidate, Sun Yat-sen Business School, Sun Yat-sen
University, No.135 West Xinggang Road, Guangzhou, 510275, China,
kenjimore@gmail.com, Fan Wang
4 - Risk Aversion and Value of Information Under Various Approaches
Onur Bakir, Visiting Assistant Professor, Bilkent University, Bilkent
Universitesi, Endüstri Mühendisligi Bölümü, Ankara, 06800, Turkey,
nonur@bilkent.edu.tr
We consider the Three-Dimensional Loading Capacitated Vehicle Routing Problem
which combines the routing of vehicles and the loading of three dimensional shaped
goods into the vehicles while minimizing the total cost. We propose a least waste
packing heuristic based approach for solving the loading subproblem, which is
iteratively invoked by a simple tabu search algorithm for the routing. Numerical
experiments on test instances have shown our method outperforms existing ones.
A previous study explored the relationship between the value of information and
risk aversion using the buying price approach. In this presentation, we discuss
whether similar conclusions hold for other approaches to evaluate information. The
information acquisition problem is analyzed in a two-action lottery setting. We
derive conditions under which there exists a monotonic relationship between the
decision maker’s risk tolerance and the value of information.
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■ WC64
■ WC66
Health Care, Processes
Miscellaneous Applications of Operations Research
Contributed Session
Contributed Session
Chair: Imran Hasan, Purdue University, 315 N Grant St., West Lafayette,
United States of America, ihasan@purdue.edu
1 - Estimation of Service Value Function
Geun Wan Park, PhD Candidate, Korea University Businsess School,
Korea Universtiry, Anam-dong, Seongbuk-gu, Seoul, 136-701,
Korea, Republic of, gw_park@hotmail.com, Kwang-Tae Park
Chair: Scott Parr, Researcher, Florida Atlantic University, 777 Glades rd.,
Boca Raton, FL, 33431, United States of America, sparr1@fau.edu
1 - Sequential Testing of K-out-of-n Systems Under
Precedence Constraints
Tonguç Unlüyurt, Sabanci University, Tuzla, Istanbul, Turkey,
tonguc@sabanciUniversityedu, Elif Ozdemir
We consider a dental clinic service as the series of service stages. We want to
estimate service value function of each service stage. The function is usually linear
function according to preexisting literatures. However, we think the function can be
different based on different service stage (for example, quadratic function or cubic
function, etc.) These functions to be estimated will be useful to determine the
service value of the dental clinic service appropriately.
We consider the minimum expected cost sequential testing problem for k-out-of-n
systems under precedence constraints. Mainly the problem is to find a feasible
strategy that produces the minimum cost binary decision tree that evaluates the kout-of-n function at hand when it is costly to learn the values of individual
variables. We summarize the results from the literature and report our initial results
of the heuristic algorithms that we develop.
2 - A Survey of the Unintended Consequences of Implementing Health
Information Technology
Shinyi Wu, Assistant Professor, University of Southern California,
3715 McClintock Ave., GER 240C, Los Angeles, CA, 90089,
United States of America, shinyiwu@usc.edu, Caitlin Hawkins
2 - Transit Signal Priority for Emergency Evacuation
Scott Parr, Researcher, Florida Atlantic University, 777 Glades rd.,
Boca Raton, FL, 33431, United States of America, sparr1@fau.edu,
Evangelos Kaisar
This research answers the question, during an urban evacuation should regional
planners allow transit units signal priority when police assisted traffic controls are
not an option. A case study of Washington D.C. shows allowing transit signal
priority (TSP) during an urban evacuation has little to no effect on evacuation
clearance time or evacuee travel time. Furthermore, four non-prioritized units are
required to accomplish the task of three prioritized vehicles.
Health information technology (HIT) has demonstrated many benefits but
unintended consequences (UCs) of its implementation cause barriers to realization.
We analyzed 215 responses to an online survey to discover the types and causes of
UCs experienced by various settings of healthcare organizations and how they coped
with them. The results showed that UCs persist over years and the most frequent
UCs are workflow problems caused by workarounds, software design, and lack of
stakeholder engagement.
3 - An Integration of Genetic Algorithm and GIS For
Sensor Optimization
Berna Dengiz, Professor, Baskent University, Baglica Kampusu
Eskisehir Road 20.km, Etimesgut, Ankara, 06530, Turkey,
bdengiz@baskent.edu.tr, Derya Oktay, Orhan Dengiz
3 - Utility of Patient Length of Stay Information
Imran Hasan, Purdue University, 315 N Grant St., West Lafayette,
United States of America, ihasan@purdue.edu, Yuehwern Yih
Emergency Department Crowding has become a major problem in ED in the
US.One of the reasons cited for this problem is the unavailability of beds in the
intensive care unit.A large number of models for the prediction of length of stay
have been developed, but there has been no research pertaining to the advantages
of such predictive models.Our goal is to evaluate the impact of knowing the LOS in
advance, and how it can help in the planning of admissions and capacity decisions
in the ICU.
This study presents a geographical information system (GIS) based procedure for the
optimization of sensor locations and sensor location parameters using genetic
algorithms (GAs). The considered problem which is a special case of the well-known
setcovering problem is NP-complete. A sensor siting optimization is an integrated
system that consists of objects used in numerous subjects which can be called as
sensor, like bare eye, camera, radar, radio, base station terminal and sensor coverage
area can be defined as viewshed (the total visibility of visible points). The sensor
operating parameters are as follows: location, height , range, azimuth, vertical
viewing angles, tilt and pitch values. Each different configuration of these
parameters results in different coverage area for a sensor. In this work, the
optimization of sensor siting mainly focus on finding out sensor sites and sensor
running parameters on terrain at the area of interest which provides maximum
coverage.
■ WC65
Inventory Management VI
Contributed Session
■ WC67
Chair: Ozden Cakici, PhD Student, University of Rochester, Carol G
Simon Hall 4th Floor, Rochester, NY, 14627, United States of America,
engin.cakici@simon.rochester.edu
1 - Managerial Application of Reducing Lead Times on Safety Stock
Zhi Tao, PhD Student, Kent State University, Dep. of M&IS, Kent,
44242, United States of America, ztao@kent.edu
Simulation III
Contributed Session
Chair: Javier Faulin Fajardo, Professor, Public University of Navarre,
Campus Arrosadia, Pamplona, 31006, Spain, javier.faulin@unavarra.es
1 - Simulation of Contribution Rates to Fund Potential U.S. State and
Federal Parental Leave Policies
Beth Neary, PhD Student, Indiana University, 1315 E. 10th St. Room 341, Bloomington, IN, 47405, United States of America,
bneary@indiana.edu
In this paper, I extend Ever’s paper (1999) by applying it to normal distribution of
lead time and demand and making interactive graphs to show the decision rule of
reducing safety stock based on the coefficient of variation of demand. Implication of
the findings on vendor managed inventory is further explored.
2 - Comparison of Continuous and Periodic Review Inventory Policies
with Continuous Time Costing
Ozden Cakici, PhD Student, University of Rochester, Carol G Simon
Hall 4th Floor, Rochester, NY, 14627, United States of America,
engin.cakici@simon.rochester.edu, Harry Groenevelt,
Abraham Seidmann
The United States is the only developed nation that lacks a national paid parental
leave program. Several U.S. states, including California, New Jersey, and soon
Washington, have instituted their own benefit programs. This project seeks to
inform state and federal policy development by simulating the costs of potential paid
leave provisions. Specifically, Monte Carlo simulation estimates payroll tax
contribution rates for varying benefit period lengths, subsidy levels, and weekly
caps.
We develop a unified analysis characterizing both periodic and continuous
inventory review policies assuming a general convex inventory related cost function
and stationary demand with independent increments. The use of continuous costing
allows us to correctly compare the economic performance of a variety of periodic
and continuous review policies, while also providing the ability to assess the impact
of tactical measures like lead time reduction and review policy changes.
2 - Simulating Team Selection Strategies for Youth Sports Programs
Stephanie Marhefka, Undergraduate Researcher, University of
Arkanas, Department of Industrial Engineering, Fayetteville, AR,
72701, United States of America, smarhefk@uark.edu,
Scott J. Mason, Ed Pohl
In this presentation we discuss several strategies for forming youth sports teams.
The goal is to find a strategy that yeilds a balnced set of teams and accounts for
pairing of coaches with children as well as skill levels of children. An Excel-Based
VBA model is used to compare three player allocation heuritic models. Once teams
are selected a season is simulated and the records of the teams are analyzed for
balance. One strategy is shown to be superior.
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3 - Calibration of Computer Models using Stochastic Approximation
Szu Hui Ng, Department of Industrial and Systems Engineering
National University of Singapore, ISE Department, NUS, Singapore,
isensh@nus.edu.sg
■ WC69
Computer models are widely used to simulate real processes. However, there always
exist some parameters which are unobservable in the real process but need to be
specified in the model. The procedure to adjust these unknown parameters to fit the
model to observed data is known as calibration. Here, we propose an effective and
efficient algorithm based on the stochastic approximation approach for calibration.
We demonstrate its feasibility and apply it to a disease microsimulation model.
Sponsored Session
Reverse Logistics I
1 - Coordination in Reverse Supply Chains: A System
Dynamics Approach
Fereshteh Mafakheri, PhD Candidate, HEC Montreal, Montreal, QC,
Canada, fereshteh.mafakheri@hec.ca, Fuzhan Nasiri
4 - Simulation of Multimodal Transport of Goods Between the Regions
Atlantic and Mediterranean in Spain
Alejandro Garcia del Valle, Professor, University La Coruna,
Mendizabal s/n, Ferrol, 15403, Spain, agvalle@udc.es, Diego Crespo
Pereira, Rosa Rios Prado, David del Rio Vilas, Javier Faulin Fajardo
A reverse supply chain is dealing with recovering a maximum value from products
at the end of their life cycle by promoting recycling, re-manufacturing, refurbishing,
and reusing activities. The objective is to protect the environment while creating
profit through material or energy recovery. In this paper, we explore a System
Dynamics approach to investigate the benefits of coordination between various
parties involved in a reverse supply chain for used printer cartridges.
The roads congestion and environmental impacts they generate are a significant
problem in developed countries. Spain has road, rail and sea: it is therefore crucial
to study the multimodal transport. The sea-road inter-modality presents an
interesting case of freight transport simulation. We will study how the goods could
be distributed among the existing infrastructure. The proposed simulation model
will address the transportation costs and the mechanisms of choice for users.
2 - Incentives and Reverse Logistics Channels with Remanufacturing
Chester Xiang, Assistant Professor, Clarkson University,
8 Clarkson Ave, Potsdam, NY, 13699, United States of America,
cxiang@clarkson.edu, Dennis Yu
■ WC68
We study a closed-loop supply chain with remanufacturing. The customer demand
is divided into two segments, i.e., business and individual customers, which show
different responses to incentives of returning used products. The reverse logistics
channels exhibit economies of scale. A third party can be used as a used-product
collecting agent. We investigate the manufacture’s incentive schemes, reverse
logistics channel strategies, and resulting financial and social impacts.
Strategy/Strategic Planning I
Contributed Session
Chair: Dale Amburgey, Director of Enrollment Analysis, Saint Joseph’s
University, 5600 City Avenue, Philadelphia, PA, 191931, United States of
America, dale.amburgey@sju.edu
1 - Temporal Fit, Misfit, and Performance: Testing Pace Entrainment in
the Movie Production Industry
Miles Zachary, Texas Tech University, RCOBA Box 42101,
Lubbock, TX, 79409, United States of America,
miles.zachary@ttu.edu, Jeremy Short, Tyge Payne
3 - Part Recovery Under Quality and Demand Uncertainty with
Environmental Costs
Gonca Yildirim, University of Florida, University of Florida,
Gainesville, FL, 32611, United States of America, gonca@ufl.edu,
Elif Akcali, Pelin Bayindir
We consider acquisition and stocking decisions, motivated by the operations of a
salvaging facility that collects a particular end-of-life product, performs a series of
disassembly and recovery operations to reclaim a reusable part and sells the
recovered part in the used parts market. We model uncertainties in demand and
quality classification of the parts and include environmental fees that create a nonnegligible tradeoff against the operational costs in acquisition and stocking decisions.
Entrainment theory is concerned with the effects of pace and/or phase
synchronizations of two or more activities within a system. This paper utilizes
entrainment theory to develop hypotheses and longitudinally test a model of
temporal fit, misfit, and performance in the movie industry in order to examine the
understudied and elusive role of time and timing’s relationship to organizational
performance.
4 - The Impact of Legislation on Product Recovery: Reuse or Recycle?
Ibrahim Karakayali, Post-doctoral Research Fellow, McGill
University, Desautels Faculty of Management, 1001 Sherbrooke St.
West, Montreal, QC, H3A1G5, Canada,
ibrahim.karakayali@mcgill.ca, Luk Van Wassenhove, Tamer Boyaci,
Vedat Verter
2 - Competitive Dynamics in Buyer-supplier Relationships
Yan Emma Liu, The University of Melbourne, Level 10, 198 Berkeley
Street, Parkville, Melbourne, Australia, yanliu@unimelb.edu.au,
Shu-Jung Sunny Yang
This paper studies the impact of co-optitive awareness on buyer-supplier
relationships. We develop a behavioral game-theoretic model, based on prospect
theory, to investigate the motivation of vertical (dis)integration. Our analysis shows
that value creation is directly proportional to downstream organization redundancy
and value appropriation is influenced by upstream organization redundancy. Our
research highlights the risk of ignoring behavioral drivers in decision making.
In this study, we develop stylized models to assess the effects of material recovery
targets (induced by legislation such as WEEE) on industry decisions pertaining to
product reusability and recycling. We conduct a comparative analysis of centralized
setting where there is cannibalization among the new and the remanufactured
products. Our analytical framework also incorporates multiple stakeholders
including the OEM, consumers, regulator, and environmentally conscious groups.
3 - The Stakeholders’ Involvement in the Strategic Planning Process
Baris Carikci, TUBITAK, Kocaeli, Kocaeli, Turkey,
bcarikci@yahoo.com
■ WC70
The tendency of Turkish public organization in favor of strategic management has
become a apparent fact in Turkey. The aim of the paper is to explain the tools to
uncover the relation between a successful strategic management process and
stakeholders’ involvement in the examples of distinguished Turkish public
institutions. With these basic tools, public sector can improve the tools they use to
initiate their stratagic management programs.
Fleet-Level Environmental Evaluation of New Aircraft
and Technologies
Sponsored Session
4 - Using Business Intelligence in College Admissions:
A Strategic Approach
Dale Amburgey, Director of Enrollment Analysis, Saint Joseph’s
University, 5600 City Avenue, Philadelphia, PA, 191931,
United States of America, dale.amburgey@sju.edu, John Yi
Chair: William Crossley, Professor, Purdue University, School of
Aeronautics and Astronautics, 701 W. Stadium Ave, West Lafayette, IN,
47907-2045, United States of America, crossley@purdue.edu
1 - Evaluating Future Environmental Impact of US Aviation via System
Dynamics and Resource Allocation
William Crossley, Professor, Purdue University, School of Aeronautics
and Astronautics, 701 W. Stadium Ave, West Lafayette, IN, 479072045, United States of America, crossley@purdue.edu
Data from first-year enrolling students were analyzed to develop predictive models.
A decision tree analysis, a neural network analysis, and a multiple regression
analysis were conducted to predict each student’s GPA at the end of the first year of
academic study. Overall model performance was evaluated by using the average
square error. Suggestions for future analysis include expansion of the study to
include more student-centric variables and to evaluate GPA at other student levels.
This study integrates system dynamics (SD) and resource allocation (RA) to evaluate
environmental impact of new aircraft and technologies. SD models observed
aviation trends and behaviors like order-delivery, price-demand elasticity, and
environmental policy dynamics. RA determines the fleet mix to maximize airline
profits subject to constraints. Results illustrate the impact of demand, policies, and
new aircraft technologies on emissions and noise over the 2005-2040 period.
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WC72
3 - A Cost-constrained Measure of Energy Efficiency
Kankana Mukherjee, Babson College, kmukherjee@babson.edu,
Subhash Ray, Lei Chen
2 - Revenue-based Allocation Model for Fleet-level Environmental
Impacts of Airline Operations
Muharrem Mane, Post-doctoral Researcher, Purdue University,
School of Aeronautics and Astronautics, 701 W. Stadium Ave,
West Lafayette, IN, 47907-2045, United States of America,
mane@purdue.edu, Dan DeLaurentis, William Crossley
We provide a measure of energy-use efficiency for a firm with cost constraints.
Using DEA, we investigate the energy efficiency of the US manufacturing sector
across states. Our results indicate that in many states the actual energy use by the
typical firm exceeds the optimal use without any increase in cost. We also find that
an effective tax on energy use in manufacturing would reduce the aggregate energy
usage while at the same time increasing the aggregate labor employment in this
sector.
This work uses a resource allocation model of airline operations to estimate the
impact that new technology and new aircraft have on fleet-level CO2 and NOx
emissions and airport noise. To approximate airline decision-making, we created a
simplified revenue model based on flight frequency and trip length. Using this in the
resource allocation objective function, we can approximate airline operations and
study the impact of aircraft-specific improvements on fleet-level environmental
metrics.
4 - Eco-efficiency Within Selected US Industries using Data
Envelopment Analysis
Paul Rouse, University of Auckland, p.rouse@auckland.ac.nz
3 - Decomposition Approach for Aircraft Allocation Under
Environmental Considerations
Isaac Tetzloff, Graduate Student, Purdue University, School of
Aeronautics and Astronautics, 701 W. Stadium Ave, West Lafayette,
IN, 47907-2045, United States of America, isaact@purdue.edu,
William Crossley
We set out to provide further empirical evidence on the relationship between firm
environmental performance and economic performance. In contrast to other studies
which have used either partial productivity measures or purely accounting ratios,
we use a frontier production model, data envelopment analysis (DEA), using
multiple inputs and multiple outputs to estimate economic performance. Using data
from four U.S. industries that are typically viewed as ‘highly environmentally
sensitive’ for a three year (2006 to 2008) period, we find some evidence that higher
levels of environmental performance are significantly associated with higher levels
of economic efficiency. Our empirical evidence is therefore broadly consistent with
the ‘Porter’ hypothesis; that is greater firm environmental performance is associated
with higher levels of economic performance. Results, however, are mixed with
positive and statistically significant coefficients on both environmental strengths and
weaknesses. We then use the Fare and Grosskopf ‘weak disposability’ framework to
explain the conflicting results in the regression analyses using the KLD strengths
and weaknesses.
Previous work to allocate aircraft amongst 257 domestic and international airports
used one large integer programming problem. Assumptions and abstractions
simplified the problem to represent a majority of commercial airline operations with
at least the arrival or destination airport in the US. Decomposing the problem into
smaller allocation problems maintains runtimes similar to the previous model, and
now includes multiple airlines, more aircraft models, and ‘one-way’ routes.
4 - Examining the Potential Environmental Impact of Legacy and
Budget Carrier Competitive Balance
Datu Agusdinata, Post-doctoral Researcher, Purdue University,
School of Aeronautics and Astronautics, 701 W. Stadium Ave,
West Lafayette, IN, 47907-2045, United States of America,
bagusdin@purdue.edu
■ WC72
Legacy and budget carriers in the US operate and compete using different business
(e.g. cost & fare structure) and operations (e.g. fleet composition, network structure,
and level of service) models. Based on a logit model to ascertain the market share of
each carrier, this study investigates how the competition may evolve over time and
assesses the resulting emissions and noise impact under multiple scenarios of
technology improvement rate, demand growth, and relative cost advantage.
Facility Logistics Interactive Session: Distribution
Center Operations
Sponsored Session
Chair: Russell Meller, Hefley Professor of Logistics and Entrepreneurship,
University of Arkansas, 4207 Bell Engineering, Fayetteville, AR, 72701,
United States of America, rmeller@uark.edu
1 - Decentralized Control of High Density Storage Systems
Kevin Gue, Associate Professor, Auburn University, Department of
Industrial & Systems Engin, Auburn, AL, United States of America,
kevin.gue@auburn.edu, Kai Furmans
■ WC71
Decision Support Models in DEA
Invited Session
We describe a decentralized control algorithm for a grid-based, high density storage
system based on the “slide puzzle architecture.” When executed with constant
work-in-process, the system provides very high throughput, and yet it consumes
less space than a typical automated storage and retrieval system.
Chair: Vladimir Krivonozhko, Institute for Systems Analysis,
KrivonozhkoVE@mail.ru
1 - DEA Models for Decision Making Support in Negotiation Process
Vladimir Krivonozhko, Institute for Systems Analysis,
KrivonozhkoVE@mail.ru, Alexander Piskunov, Andrey Lychev,
Maria Piskunova
2 - The Fishbone Triangle Design for Dual-Command Cycles in a
Unit-Load Warehouse
Russell Meller, Hefley Professor of Logistics and Entrepreneurship,
University of Arkansas, 4207 Bell Engineering, Fayetteville, AR,
72701, United States of America, rmeller@uark.edu, Letitia Pohl,
Kevin Gue
In this paper, an approach is proposed on evaluation of agreements on transnational
projects during the negotiation process. One can show that the negotiation process
can be represented as the behaviour of decision making units (countries) in the
multidimensional space of economic indicators using DEA models. In this case, the
goals that can be reached by units as a result of accomplishment of joint project can
be determined as points in the multidimensional space. Optimal directions toward
these goals and cones of possible directions can be found with the help of Analytic
Hierarchy Process (AHP). Our approach is illustrated on the real-life data taken from
open international sources.
The fishbone warehouse design improves upon traditional warehouse designs for
single-command cycles, but is not as efficient for the travel-between leg of a dualcommand cycle. The fishbone triangle design was developed to address this issue.
We have developed a set of analytical expressions for travel-between in the fishbone
triangle warehouse, which allows us to optimize this non-traditional warehouse
design. We will present results on its performance.
3 - Determining the Optimal Aisle-width for a Semi-automated Picking
System in a Distribution Center
Pratik Parikh, Assistant Professor, Wright State University,
3640 Col Glenn Hwy, 207 Russ Eng Center, Dayton, OH, 45435,
United States of America, pratik.parikh@wright.edu, Sheena Finney
2 - The Winner is Kobe: Site Selection for the Next-generation
Supercomputing Center in Japan
Kaoru Tone, National Graduate Institute for Policy Studies, Japan,
tone@grips.ac.jp
The Next Generation Supercomputer R&D Project is an endeavor to create a 10
Pflop/s system by 2012. It will be considered to be one of the “Key Technologies of
National Importance of Japan.” Its goals are: (1). Development and installation of
the most advanced high performance supercomputer system; (2). Development and
wide use of application software to utilize the supercomputer to the maximum
extent; (3) Provision of a flexible computing environment by sharing the next
generation supercomputer through connection with other supercomputers ; (4)
Establishment of an “Advanced Computational Science and Technology Center.” In
this talk, I will report how the site selection was decided using AHP and DEA.
We consider the aisle-design problem for a semi-automated picking system that uses
a person-on-board material handling equipment, such as an order picker truck.
Using a previously developed model to determine the optimal storage level for such
a system, we conduct a simulation study to determine the aisle-width (narrow or
wide) that minimizes total system cost. We also compare our results with those
obtained for a manual system to generate managerial insights when designing such
systems.
433
WC73
4 - A Network Model for Warehouses with Non-Traditional Aisles
Omer Ozturkoglu, Auburn University, Department of
Industrial&Systems Engineering, Auburn, AL, 36849, United States
of America, ozturom@auburn.edu, Kevin Gue, Russell Meller
2 - Environmental Risk Analysis of Railroad Transportation of
Hazardous Materials
Rapik Saat, Postdoctoral Research Associate, University of Illinois at
Urbana-Champaign, 205 N Mathews RM3214, Urbana, IL, 61801,
United States of America, mohdsaat@illinois.edu, Chris Barkan
We show how to construct non-traditional aisle designs for unit-load warehouses
with multiple pickup and deposit (P&D) points, using a network model to represent
storage locations and P&D points. The model uses a meta-heuristic to search for
optimal angles of cross aisles and picking aisles.
This presentation will describe a quantitative risk analysis of rail transportation of
hazardous materials using an environmental consequence model in conjunction
with a geographic information system (GIS) exposure analysis along the U.S. rail
network. The annual risk estimate incorporates the estimated remediation cost,
route-specific probability distributions of soil type and depth to groundwater, annual
traffic volume, railcar accident rate, and tank car safety features.
■ WC73
3 - Dual Toll Pricing for Hazardous Material Transport with Linear Delay
Jiashan Wang, University at Buffalo- SUNY, Department of Industrial
Engineering, Buffalo, NY, United States of America,
jw282@buffalo.edu, Yingying Kang, Rajan Batta, Changhyun Kwon
Joint Session TSL/ SPPSN: Methods to Support
Regional Evacuation
We propose a dual toll pricing method to mitigate risk of hazmat transportation. We
aim to control both regular and hazmat vehicles to reduce the risk. We incorporate
a new risk measure to consider duration-population-frequency of hazmat exposure.
We formulate the model as an MPEC problem and then decompose the formulation
into first-stage and second-stage problems. For each stage problem, we present
methods to solve them separately. A numerical example is provided.
Sponsored Session
Chair: Irina Dolinskaya, Assistant Professor, Northwestern University,
2145 Sheridan Road, M235, Evanston, IL, 60208, United States of
America, dolira@northwestern.edu
1 - Design of an Evacuation Network for Hurricane Evacuation
Xinghua Wang, Texas A&M University, 303K Zachry, TAMU,
College Station, United States of America, wxh55@tamu.edu,
Justin Yates, Halit Uster
Wednesday, 3:30pm - 5:00pm
■ WD01
We consider large scale evacuations in expected extreme event situations such as
hurricanes. We present a mixed integer model to minimize total costs under time
constraints while determining associated facility locations and traffic flows to
construct evacuation routes. We develop a Benders decomposition based solution
approach and report numerical results using Texas-based real data facilitated by GIS.
Joint Session ENRE/ QSR: Renewable Energy
Integration into Power Systems for Smart Operations
2 - An Integrated Demand-Supply Framework for
Evacuation Operations
Yu Ting Hsu, Purdue University, West Lafayette, IN,
United States of America, yhsu@purdue.edu, Srinivas Peeta
Sponsor: Energy, Natural Resources and the Environment/ Quality,
Statistics and Reliability
Sponsored Session
Chair: Eunshin Byon, PhD, Postdoctoral Research Associate, Texas A&M
1 - Optimizing the Acquisition and Operation of On-site
Electricity Generation
Kris Pruitt, kpruitt@mymail.mines.edu, Rob Braun,
Alexandra Newman
Evacuation operations involve perspectives from both the demand and supply sides.
This study proposes an integrated operational framework to address the interactions
between evacuation flow management and individual behavior, by using robust
evacuation behavior models that consider the various factors that influence
evacuation-related decision-making.
3 - Large-Scale Evacuations with Arc Routing
Mark Hickman, Associate Professor, University of Arizona, Civil
Engineering, 1209 E. Second St., Bldg 72, Tucson, AZ, 85721-0072,
United States of America, mhickman@email.arizona.edu,
Moshe Dror
We present a mixed-integer, nonlinear program for designing and operating an onsite generation system to supply electricity to a large, commercial building. The
system design includes renewable and non-renewable generation, net-metering to
the grid, and on-site storage. The model determines the optimal mix of generators
and storage units to acquire, along with their operating levels over time, to
minimize total cost subject to system performance characteristics and the building’s
demand.
We consider a routing of public vehicles to evacuate persons during a large-scale
emergency. To facilitate the evacuation, we consider a routing of vehicles along
roadways to pick up people at their residences or other locations. We present an arc
routing model for this case and illustrate the model on a large-scale case study.
2 - Simulation and Optimization of Wind Farm Operations Under
Stochastic Conditions
Eunshin Byon, PhD, Postdoctoral Research Associate, Texas A&M
■ WC74
Hazardous Material Transportation
This research aims at developing models and associated solution tools to devise
optimal maintenance strategies for wind turbines, helping reduce the operation
costs and enhancing the marketability of wind power. We provide an integrated
framework including optimization models, and a discrete event-based simulation
model characterizing the dynamic operations of wind power systems. We highlight
the benefits of the resulting strategies through a case study.
Sponsored Session
Chair: Changhyun Kwon, Assistant Professor, University at Buffalo,
400 Bell Hall, Buffalo, NY, 14260, United States of America,
chkwon@buffalo.edu
1 - Value-at-Risk Model for Hazmat Transport
Yingying Kang, PhD Candidate, University at Buffalo - SUNY,
Department of Industrial Engineering, 438 Bell Hall, Buffalo, NY,
14260, United States of America, ykang4@buffalo.edu, Rajan Batta,
Changhyun Kwon
3 - Reliability Evaluation of Wind Turbine via Computer Simulation and
Laboratory Experiments
Haitao Liao, Assistant Professor, The University of Tennessee, 211
Pasqua Building, Knoxville, TN, 37996, United States of America,
hliao4@utk.edu, Seyed Ahmad Niknam, Janet Twomey
It is important to ensure the long-term reliability of wind generators for secured,
uninterrupted power extraction from the wind. This research aims at evaluating the
reliability of wind generators in time-varying environments via computer simulation
and laboratory experiments.
We propose a new measurement of risk in hazmat transportation, namely Value-atRisk (VaR). The VaR measurement aims to gauge the cutoff risks within a certain
confidence level, instead of minimizing the expected risk or maximal risk of a
hazmat path directly. This allows the choice of a hazmat route according to decision
makers’ risk preferences. Furthermore, we display that the route choice with the
VaR model depends on the level of risk tolerance.
434
■ WD02
WD04
2 - Interactive Evolutionary Multi-Criteria Scheduling
Jon Marquis, Senior Systems Engineer, Raytheon, 1151 East
Hermans Road, Tucson, AZ, 85756, United States of America,
jonemailbox1@gmail.com, John Fowler, Esma Gel, Pekka Korhonen,
Jyrki Wallenius, Murat Köksalan
Energy II
Contributed Session
We present a new approach to multi-criteria scheduling using an interactive
evolutionary algorithm with a scheduling heuristic to develop solutions. The
algorithm sends a subset of the solutions to the decision maker (DM) for evaluation
and uses the resulting preference information to evaluate new solutions and guide
the algorithm. We apply the algorithm to the weighted completion time, total
tardiness, and maximum lateness criteria.
Chair: Nicolas Lopez, Research Assistant, The University of Texas at
El Paso, 500 West University Avenue, El Paso, TX, 79902,
United States of America, nlopez3@miners.utep.edu
1 - Incorporating Gas Pricing Into Oil & Gas Asset Development
Planning - An Example
Chaiyaporn Wiboonkij-Arphakul, Decision Analyst, Chevron, Tower
III, SCB Park Plaza, 19 Ratchadapisek Rd, Chatuchak, Bangkok,
10900, Thailand, cwiboonkij@gmail.com, Ing Jye Tsai
3 - Solving Multiobjective Mixed Integer Programs using Convex Cones
Murat Köksalan, Middle East Technical University, ODTU 06531,
Ankara, Turkey, koksalan@ie.metu.edu.tr, Jyrki Wallenius,
Banu Lokman, Pekka Korhonen
As gas is sold in the $ per BTU, there is a clear incentive for one to maximize profits
by accelerating the development of high-BTU wells. However, doing so in some
environment (e.g., under Gas Sales Agreement) may lead to the loss of low-BTU gas
reserves and the delivery shortfall penalty. For Chevron Thailand, profit is
maximized through the ranking of drilling projects’ profitability index while BTU
forecast is only used to ensure that future production meets contractual
specifications.
We assume that the decision maker’s preferences are consistent with a quasiconcave
utility function. Based on the convex cones derived from past preferences, we create
constraints to prevent solutions in the implied inferior regions. We guarantee
finding the most preferred solution and our computational results show that a
reasonable number of pairwise comparisons are required.
2 - A Framework to Integrate Renewable Energy to Improve the Energy
Efficiency: An OR Application
Haifeng Wang, IBM Research - China, Building19, Zhongguancun
Software Park, 8 Dongbeiwang West Rd, Haidian District, Beijing,
China, whf@cn.ibm.com, Wenjun Yin, Jin Dong, Feng Gao
■ WD04
Sustainability II
This paper focuses on developing a framework for smart grid to utilize weather and
renewable energy production forecasting to help integrate distributed renewable
energy and energy storage into the electric distribution and transmission system. A
demand-supply matching model is developed, in which power demand is modeled a
given stochastic process, and the optimal unit planning policy is researched.
Moreover, the renewable energy efficiency is evaluated for different feasible policies.
Contributed Session
Chair: Amrou Awaysheh, Assistant Professor of Operations Management,
IE Business School, Maria de Molina, 12 - 5 planta, Madrid, 28006,
Spain, amrou.awaysheh@ie.edu
1 - The Impact of Green Vehicles on the Market Value of Automakers
Qindong Liu, University of Connecticut School of Business,
2100 Hillside Road, Storrs, CT 06269, United States of America,
qindong.liu@business.uconn.edu, Jan Stallaert
3 - A Greedy Approach to Scheduling Outage Tasks for Distribution
Power Network
Ming Zhao, IBM Research - China, Diamond building, ZGC Software
Park, Haidian District, Beijing, 100193, China,
papayazm@gmail.com, Feng Jin, Hairong Lv, Qiming Tian, Jin Dong,
Wenjun Yin
We conduct an event study to explore how stock markets react to automakers’ fuelefficient product strategies. We find automakers’ green technology and product
innovations have a positive impact on their market valuation, although the
technology and market segment choices have different implications. The abnormal
returns could be explained by both internal and external factors. More interesting,
our analysis indicates that product design variables moderate those relationships.
Because of the complexity of distribution power network, outage task scheduling
problem is usually large-scale, which results in unpractical long running time for
many traditional methods. In this paper, combination weight between different
tasks was defined. Then, a weight-based greedy algorithm was proposed to facilitate
the procedure. In this way, computational complexity was reduced from O(t^n) to
O(tn). Test results on a real distribution system show the efficiency of the approach.
2 - A LCA Method Considering Multi-Scenario and System Uncertianty
Jianzhi Li, Assistant Professor, The University of Texas - Pan
American, 1201 W University Dr., Edinburg, TX, 78539,
United States of America, jianzhi.li06@gmail.com, Xiaowei Wang
4 - Hybrid Power Systems Optimization Considering Different
Renewable Energy Technologies
Nicolas Lopez, Research Assistant, The University of Texas at El Paso,
500 West University Avenue, El Paso, TX, 79902, United States of
America, nlopez3@miners.utep.edu, Jose Espiritu
Current LCA approaches failed to consider spatial and temporal system uncertainty
in its calculation. A new LCA method is proposed which considers uncertain future
multi-scenario. The LCI data are collected as per scenario including pollution
emissions and character information that are used to generate personal, spatial and
temporal factors, which reflect the diversity of environment. The impacts is obtained
by summing up the results of each scenario wighted by the scenario probabilities.
Hybrid power systems need to be evaluated based on the requirements of high
penetration renewable energy technology applications. Additionally, modeling and
analysis storage systems integration are also necessary to increase the effectiveness
of hybrid power configurations. In the present talk, a software based simulation to
understand the Hybrid power systems response considering various renewable
energy technologies and energy storage options is presented.
3 - The Impact of Social Issues Management on Firm Performance An Event Study
Amrou Awaysheh, Assistant Professor of Operations Management, IE
Business School, Maria de Molina, 12 - 5 planta, Madrid, 28006,
Spain, amrou.awaysheh@ie.edu, Robert D. Klassen
The management of social issues can have a substantial impact on a firm’s financial
performance. Social issues are complex, and managing them requires a range of
practices. Examples include establishing workforce policies for safe work practices or
diversity; however, a firm may also be involved in negative practices, such as the
use of illegal labor practices. This paper will present the results from an ongoing
event study that examines the impact of social issues management on a firm’s value.
■ WD03
Interactive Multiple Criteria Decision Making
Sponsor: INFORMS Section on Multiple Criteria Decision Making
Sponsored Session
Chair: Murat Köksalan, Middle East Technical University, ODTU 06531,
Ankara, Turkey, koksalan@ie.metu.edu.tr
1 - An Interactive Approach for MCDM using a Hybrid
Tchebycheff/Linear Utility Function
Ozgen Ozbey, SUNY Buffalo, 308A Bell Hall, Department of
Industrial and Systems Eng, Buffalo, 14260-1900, United States of
America, oozbey2@buffalo.edu, Mark H. Karwan
We improve our previously developed MILP formulation to estimate a Decision
Maker’s (DM) utility function used during an interactive method employing
pairwise comparisons. The utility function is approximated by a Tchebycheff or
hybrid function with Tchebycheff and linear components. We consider a DM’s
precision and “strength of preferences” to obtain a most preferred solution among
implicit alternatives in an effective manner. We present computational results and
comparisons with other methods.
435
WD05
■ WD05
■ WD07
Dynamic Programming/Control II
Supply Chain, Closed-loop II
Contributed Session
Contributed Session
Chair: Suleyman Demirel, PhD Candidate, Ross School of Business,
University of Michigan, 701 Tappan Ave, Ann Arbor, MI, 48104,
United States of America, sdemirel@umich.edu
1 - Ad Valorem Tax and the Cumulated Output of
Exhaustible Resources
Runfang Xu, PhD Candidate, Xi’an Jiaotong University, No.28,
Xianning West Road, Xi’an, 710049, China, runfangxu@yahoo.com,
Xinmei Liu
Chair: Jo Min, Iowa State University, IMSE Department, 3004 Black,
Ames, IA, 50011, United States of America, jomin@iastate.edu
1 - Hybrid Manufacturing/Remanufacturing System in Cascade Reuse
Yasutaka Kainuma, Tokyo Metropolitan University, 6-6, Asahigaoka,
Hino, Tokyo, 191-0065, Japan, kainuma@sd.tmu.ac.jp
In this research, we constructed a cascade reuse hybrid
manufacturing/remanufacturing model. We proposed the optimal ordering policy
minimizing manufacturer’s total costs when manufacturing two grades of products.
In the data examples, comparing the proposal policy with the policy of the actual
operations of company-A, we could confirm the optimality of the proposal policy.
This paper, after modifying the Hotelling model and using the dynamic control
method, researches the relation between ad valorem tax and cumulated output of
exhaustible resources under monopoly. It is shown that the cumulated output is
lower than perfect competition when the ad valorem tax rate equals to zero. And
the cumulated output is decreased more when the ad valorem tax rate more than
zero. However, the cumulated output is increased when the ad valorem tax rate less
than zero.
2 - Joint Inventory-promotion Decision in Closed-loop Hybrid
Manufacturing System
S. Phil Kim, PhD Candidate, Purdue University, 315 N. Grant Street,
ksphil@purdue.edu, Seokcheon Lee, J. George Shanthikumar
2 - Sensitivity-Based Nested Partitions for Solving Markov
Decision Processes
Weiwei Chen, University of WIsconsin-Madison, 1513 University
Avenue, Madison, WI, 53706, United States of America,
wchen26@wisc.edu, Leyuan Shi, Yanjia Zhao, Xiaohong Guan
In this paper, Markov decision process is used for the joint inventory-promotion
decision problem in a closed-loop hybrid system. The stochastic returns are
correlated with the volume of circulation. The demands are also stochastic and
influenced by the promotion decision. The state space can be divided into
promotion-desired and promotion-not-desired spaces. For a given decision on the
promotion, we show that the optimal solution structure is completely defined by
two points in the state space.
This paper introduces an algorithm to solve finite-horizon total-cost Markov
decision processes with non-stationary policies. It is based on Nested Partitions (NP)
global optimization framework, and combines the search power of a local optimizer
using sensitivity-based analysis. An intelligent partitioning approach is developed to
determine the new partitions adaptively based on the information from previous
iterations. The numerical example shows the effectiveness of the proposed
algorithm.
3 - ANP Methodology and Reverse Supply Chain
Sharon Ordoobadi, University of Massachusetts, 285 Old westport
Road, Dartmouth, United States of America, sordoobadi@umassd.edu
The objective is development of a decision tool to help with selection of the third
party reverse logistics provider. The criteria to be considered in the evaluation
process are identifgied. The ANP methodology is applied to rank the potential
providers. The provider with the highest ranking is chosen to perform the reverse
logistic function.
3 - Dynamic Airline Asset Allocation Incorporating Econometric
Demand Models
Navindran Davendralingam, Purdue University, School of
Aeronautics and Astronautics, 701 West Stadium Avenue, West
Lafayette, 47906, United States of America, davendra@purdue.edu,
William Crossley
4 - Closed-loop Supply Chain with Dynamic Returns and Incentives
Pietro De Giovanni, NOVA School of Business and Economics,
Campus Campolide, 1099, Lisbon, Portugal,
pietro.degiovanni@fe.unl.pt
Operational adjustments by airlines translate to latent passenger observations who
dictate future demand trends based on cost feasibility and ancillary benefits offered
by various ticket itineraries being published. The current proposed research develops
a conceptual dynamic framework that builds upon previous paradigms in dynamic
programming, econometrics and system engineering to maximize revenue for a
given airline using tactical asset allocation subject to reflexive demand feedback.
In a closed-loop supply chain (CLSC), a single manufacturer and a single retailer
invest in green activities to enhance the product return. Coordination is evaluated
by means of a pay-back contract while the return policy is managed in an active
manner. The return rate is thus modeled as a dynamic equation that evolves over
time according to the green activities. We investigate the conditions under which
coordination is Pareto-improving.
4 - Resource Taxation and the Cumulated Output of Exhaustible
Resource Under the Externality
Runfang Xu, PhD candidate, Xi’an Jiaotong University, No.28,
Xianning West Road, Xi’an, 710049, China, runfangxu@yahoo.com,
Xinmei Liu
5 - Product Weight Reduction Investment and Collection Rate in a
Closed Loop Supply Chain
Jo Min, Iowa State University, IMSE Department, 3004 Black, Ames,
IA, 50011, United States of America, jomin@iastate.edu, Wenbo Shi,
Karla Valenzuela
How to enhance cumulated output and how to lengthen the total lifetime of
exhaustible resources is a very popular topic. Firstly, this paper constructs a dynamic
optimal control model under the condition of externality. Secondly, this paper,
applying simulation, analyses the relationship between resource taxation and
cumulated output and total lifetime. Finally, the results are confirmed by data from
China.
We investigate a Stackelberg game consisting of a manufacturer/remanufacturer
who directly sells to customers and a collector of the used products. The collector is
the follower who determines the collection rate and the manufacturer is the leader
who determines the price and the product weight reduction investment. As the cost
saving of remanufacturing increases, the product weight and collection rate both
increase. i.e., the environmental policies of reduce and reuse may be selfcontradictory.
5 - Production and Inventory Control for a Two-Stage Assemble-toOrder System with Uncertain Capacities
Suleyman Demirel, PhD Candidate, Ross School of Business,
University of Michigan, 701 Tappan Ave, Ann Arbor, MI, 48104,
United States of America, sdemirel@umich.edu, Roman Kapuscinski,
Izak Duenyas
Consider a firm assembling product from subcomponents, where both assembly
capacity and subassembly capacities are uncertain. The assembly capacity is
common, while each component has dedicated subassembly resources. The firm
may hold inventory of subassemblies. We analyze a multi-period inventory model
for two products, and derive the optimal replenishment policy of the subassemblies
as well as the optimal priority scheduling of the assembly resource.
436
■ WD08
WD10
2 - Bounded Rationality in Service Systems
Tingliang Huang, Kellogg School of Management, Northwestern
University, Leverone 529, Jacobs Center, 2001 Sheridan Road,
Evanston, IL, 60208, United States of America, tinglianghuang@kellogg.northwestern.edu, Achal Bassamboo, Gad Allon
Facility Location II
Contributed Session
The traditional economics and queueing literature typically assume that customers
are fully rational. In contrast, in this paper, we study canonical service models with
boundedly rational customers. We capture bounded rationality using a framework
in which better decisions are made more often, while the best decision needs not
always be made.
Chair: Jiamin Wang, Associate Professor, Long Island University, Roth
Hall 202, Long Island University, 720 Northern Blvd, Brookville, 11548,
United States of America, jiamin.wang@liu.edu
1 - A Heuristic Procedure for the Integrated Facility Layout Design and
Flow Assignment Problem
Seyed Ali Taghavi, Wayne State University, 4815 Fourth Street,
detroit, MI, 48202, United States of America, dz3738@wayne.edu,
Alper Murat
3 - Hyperbolic Discounting in a Service System: Implications for Pricing
& Information Provision
Erica Plambeck, Professor, Stanford Graduate School of Business, 518
Memorial Way, Stanford, CA, 94305, United States of America,
plambeck_erica@GSB.Stanford.Edu, Qiong Wang
We study integrated lay-out design problem and product flow assignment problem.
The lay-out design decisions involve planar location of unequal-area machines with
duplicates. The product flows are assigned to machines according to the product
processing routes. We propose a heuristic procedure based on the alternating
location-assignment heuristic. Then, we apply a perturbation algorithm to escape
local optima. A sequential location heuristic is also used to speed up the location
problem.
People often lack the self control to undergo an unpleasant service that would be in
their long-run self interest. This “hyperbolic discounting” has implications for
optimal pricing, scheduling and whether or not to give a customer real-time
information about how long he must wait to complete service.
4 - Advance Selling When Consumers Regret
Javad Nasiry, HKUST, Clear Water Bay, Kowloon, Hong Kong, Hong
Kong, Hong Kong - PRC, Javad.NASIRY@insead.edu, Ioana Popescu
2 - Application of Hybrid Analysis of a Discrete Space Location in a
School Location Problem
Farshad Majzoubi, PhD Student, University of Louisville, Department
of Industrial Engineering, JB Speed School of Engineering,
Louisville, KY, 40292, United States of America,
f0majz01@louisville.edu, Bulent Erenay, Trivikram Rao
We develop a model to capture the emotional consequences of decision making
under uncertainty. Negative outcomes trigger regret as consumers reflect ex-post
what would have been had they decided alternatively. We investigate how regret
affects consumers’ behavior and how firms can account for consumer regret in
designing their pricing policies.
This research develops a generic Excel model using the Hybrid Analysis method for
discrete space location problems, and combines it with an Analytical Hierarchy
Process approach to act as a decision support tool to select the optimal location to
open a school when both quantitative and qualitative factors are involved.
Keywords: Location allocation, Hybrid analysis, Analytical Hierarchy Process
■ WD10
3 - A Minimax Approach to EMS-Helicopter Station and Heliport
Location Problems
Takehiro Furuta, Dr., Assistant Professor, Tokyo University of
Science, 1-3 Kagurazaka, Shinjuku-ku, Tokyo, 162-8601, Japan,
takef@fw.ipsj.or.jp, Ken-ichi Tanaka
Pricing Issues in Supply Chain Management
Sponsored Session
Chair: Srinagesh Gavirneni, Cornell University, 325 Sage Hall, Ithaca, NY,
14853, United States of America, nagesh@cornell.edu
1 - Pricing and Logistics Decisions for a Private-Sector Provider in the
Cash Supply Chain
Mili Mehrotra, Assistant Professor, University of Minnesota, 321
19th Ave. S, Carlson School of Management, Minneapolis, MN,
United States of America, milim@umn.edu, Vijay Mookerjee,
Chelliah Sriskandarajah, Milind Dawande
We propose location models for EMS-helicopter systems. The helicopters require
their stations and heliports to pick up patients. We formulate the model as an
integer programming problem which seeks to find locations of both stations and
heliports to minimize the maximum transportation time. Our model is applied to
analyzing optimal locations using an idealized city model under various
assumptions.
4 - A Median Problem on a Network with Random Travel Speeds and a
Desirable Travel Time Level
Jiamin Wang, Associate Professor, Long Island University, Roth Hall
202, Long Island University, 720 Northern Blvd, Brookville, 11548,
United States of America, jiamin.wang@liu.edu
For secure-logistics providers, the Fed’s cash recirculation policy presents an
opportunity to offer fit-sorting services to Depository Institutions. We address the
logistics and joint pricing of the new fit-sorting and the traditional transportation
services. We characterize the behavior of the optimal prices and quantify the impact
of the logistics network.
We consider a facility location problem on a network when the travel speeds along
links are discrete random variables. For each customer, a utility “loss” incurs if
travel time to reach a facility is beyond a desirable level. The objective is to locate
facilities so as to maximize the expected total customer utility. A dominant point set
is identified and solution methods are developed. It is also shown that some classic
deterministic models are special cases of the problem under study.
2 - The Multi-Product Newsvendor Problem with
Customer-Driven Substitution
Joonkyum Lee, Cornell University, 301A Sage Hall, Cornell
University, Ithaca, NY, 14853, United States of America,
jl883@cornell.edu, Amr Farahat
We study the stocking problem faced by a newsvendor offering multiple
substitutable products where a customer’s probability of choosing any given product
depends on the set of available products at the time of purchase. We present a
tractable method that is guaranteed to yield an upper bound on the optimal
expected profit. Numerical tests show that the true expected profits of the solutions
obtained typically lie within a few percentage points of the upper bound and often
outperform benchmarks.
■ WD09
Service Operations
Sponsored Session
3 - Robust Pricing with Two Substitutable Products
Zhi-Long Chen, Professor, University of Maryland,
Robert H. Smith School of Business, College Park, MD, 20742,
United States of America, ZChen@rhsmith.umd.edu, Ming Chen
Chair: Gad Allon, Northwestern University, 2001 Sheridan Road,
Evanston, IL, United States of America, gallon@kellogg.northwestern.edu
1 - The Concert Queuing Arrivals Game: Finite Customer Analysis
Sandeep Juneja, Associate Professor, Tata Institute, HB Road, Colaba,
Mumbai, 400005, India, juneja@tifr.res.in, Nahum Shimkin
We study a dynamic pricing problem involving two substitutable products. Given
limited demand information, we use three types of bounds to model demand
uncertainty. We propose a robust optimization approach for the problem and
develop a fully-polynomial time approximation scheme based on a DP formulation.
We report computational results and related managerial insights on how the optimal
prices change with model parameters.
We consider a queuing system where a finite number of customers arrive. Each
customer is free to choose her arrival time (before or after the opening time) and is
interested in early service completion with minimal wait. We analyze the
equilibrium behavior of this system and study its convergence to the associated fluid
limit as the number of customers increases to infinity.
437
WD11
4 - Quality, Inspection, and Pricing Policies in Supply Chains
Murat Erkoc, Assistant Professor, University of Miami, Miami, FL,
United States of America, merkoc@miami.edu, Haresh Gurnani
2 - The Impact of Category Captainship on Retail Assortment
and Consumers
Mumin Kurtulus, Assistant Professor, Vanderbilt University,
Owen Graduate School of Management, 401 21st Avenue South,
Nashville, TN, 37203, United States of America,
mumin.kurtulus@owen.vanderbilt.edu, Alper Nakkas
We consider a decentralized supply chain where market demand depends on the
supplier’s quality investment and the buyer’s inspection policies. The supplier
chooses the quality level and the wholesale price, whereas the buyer sets the
inspection policy and the resale price. Building quality raises costs for the supplier
and inspection is costly for the buyer. However, they reduce external and internal
failure costs. We investigate equilibrium quality investment, inspection, and pricing
policies.
Category captainship is a practice where a retailer relies on one of the leading
manufacturers in the category for recommendations on retail assortment. In this
paper, we investigate the impact of category captainship on the assortment offered
at the retailer and its impact on the consumers. We identify the conditions under
which category captainship practices can hurt the consumers.
3 - Pricing Policy in a Supply Chain: Negotiation or Posted Pricing?
Goker Aydin, Associate Professor, Indiana University, Kelley School
of Business, Bloomington, IN, 47405, United States of America,
ayding@indiana.edu, Hyun-Soo Ahn, Chia-wei Kuo
■ WD11
Green Supply Chains
Chair: Feryal Erhun, Stanford University, 380 Panama St, Stanford, CA,
94305, United States of America, ferhun@stanford.edu
This paper examines the choice between posted pricing and negotiation when
selling to the end customers. We find that the retailer and the manufacturer
disagree only when the retailer prefers posted pricing, but the manufacturer wishes
the retailer to use negotiation. Such friction arises when the capacity or the cost of
negotiation is moderate. Surprisingly, in this region of friction, a decrease in capacity
or an increase in negotiation costs translates into higher profit for the retailer.
Co-Chair: Tim Kraft, Stanford University, 920 South California Avenue,
Palo Alto, CA, 94306, United States of America, tkraft@stanford.edu
1 - Effect of Carbon Emission Regulations on Transport Mode Selection
in Supply Chains
Tarkan Tan, T.Tan@tue.nl, Kristel Hoen, Jan Fransoo,
Geert-Jan Van Houtum
4 - Motivating Marketing Effort Under Price Delegation: Optimal Retail
Contract Design
Shanshan Hu, Asst Professor, Indiana University, Kelley School of
Business, 1309 E 10th St, Bloomington, IN, 47405, United States of
America, hush@indiana.edu, Wenbin Wang, Xinxin Hu,
Robert Jacobs
We investigate the effect of two regulation mechanisms to drive down carbon
emissions on the transport mode selection decision: an emission cost and an
emission constraint. We use an accurate calculation method to determine the
carbon emissions and incorporate them explicitly in our model. Our results show
that introducing an emission cost for freight transport, e.g. via a market mechanism
such as cap-and-trade, will not result in large emission reductions.
Motivated by the interaction between an appliance manufacturer and its regional
retailers, this paper investigates the contract design problem for the manufacturer.
We provide answers to three related questions: (a) how to elicit actual demand
information from the retailer, (b) how to motivate retailer to promote sales, and (c)
how to construct the contract through relatively simple terms used in practice.
2 - The Carbon-Constrained EOQ
Saif Benjaafar, Professor, University of Minnesota, 111 Church Street
SE, Minneapolis, United States of America, saif@umn.edu, Xi Chen
■ WD15
Sponsored Session
We examine the impact of carbon emission consideration on the management of
inventory systems. We do so in the context of the classic economic order quantity
model (EOQ). We incorporate carbon emission considerations by accounting for
emissions associated with ordering, purchasing, inventory holding, and sales. We
examine how different emission control policies (such as strict caps, carbon taxes,
and carbon trading) affect ordering decisions and the corresponding costs and
emission levels.
Organization Theory II
Contributed Session
Chair: Christopher Rump, Associate Professor, Bowling Green State
University, Applied Statistics & Operations Research, Bowling Green, OH,
43403, United States of America, cmrump@bgsu.edu
1 - Assembly of Successful Teams: Insights From the
Study of MMORPGs
Mengxiao Zhu, Northwestern University, 2145 Sheridan Rd, C210,
mzhu@northwestern.edu, Noshir Contractor, Seyed Iravani
3 - Replacement Decisions for Potentially Hazardous Substances
Tim Kraft, Stanford University, 920 South California Avenue, Palo
Alto, CA, 94306, United States of America, tkraft@stanford.edu,
Dariush Rafinejad, Feryal Erhun, Robert Carlson
As public awareness of environmental hazards increases, a growing concern for
firms is the negative environmental impact of their products. We study the decisions
of firms and stakeholders when a substance within a product is considered
potentially hazardous. We find large firms should plan their replacement decisions
to avoid costs, while small firms should invest to establish niche market positions. In
addition, NGOs and regulatory bodies should take a pragmatic approach when
pressuring firms.
Teamwork is crucial to accomplish difficult tasks successfully and efficiently. This
paper investigated the influence of compositional and structural factors on team
performance. Compositional factors are related to the attributes of team members,
such as expertise diversity and demographic homophily. Structural factors measure
the intra/inter team social structures of formal and informal relations. An analysis of
MMORPG combat teams identifies the impact of these factors on team performance.
2 - Developing Innovative Capabilities in Biotechnology Firms:
Internal Building and External Leveraging
Yuanyuan Wu, Doctoral Student, McGill University, Desautels
Faculty of Management, 1001 Sherbrooke Street W., Montreal, QC,
H3A1G5, Canada, yuanyuan.wu@mail.mcgill.ca, Paola Perez-Aleman
■ WD12
Different Approaches to Demand Management in Retail
This paper explores the initiation and development of innovative capabilities in
Montreal-based biotech firms through a multiple-case study design. The existing
literature separately focuses on internal resources or network leveraging. By
contrast, this study combines these two aspects, and uncovers different implications
of the combination on the path and pace of capability development. The results
extend the role of collaboration in firms with different nature and timing patterns.
Supply Chain
Sponsored Session
Chair: Gilvan Souza, Associate Professor, Indiana University, Kelley
School of Business, 1309 E 10th St, Bloomington, IN, 47401, United
States of America, gsouza@indiana.edu
1 - Shelf Loathing: Cross Docking at an Online Retailer
Kyle Cattani, Associate Professor, Indiana University, Kelley School
of Business, 1309 E 10th St, Bloomington, IN, 47405, United States
of America, kcattani@indiana.edu, Gilvan Souza, Shengqi Ye
3 - The Evolution of Product Categories: How ‘Spaghetti’ Western
Impacted American Western Movies
Moritz Fliescher, PhD Candidate, New York University, Leonard N.
Stern School of Business, 44 West 4th Street, Room 7-157,
New York, NY, 10012, United States of America,
moritz.fliescher@stern.nyu.edu, Gino Cattani
We analyze basic trade-offs inherent in cross-docking transactions at an online
retailer. Rather than picking the item from inventory on the warehouse shelves, in
a cross-docking transaction the item moves directly from the receiving dock to the
shipping dock. While the cross-docking transaction reduces the shelving and picking
costs, it potentially increases holding costs and risks changing the customer’s
expectations for how soon a product will be delivered.
We add to the category dynamics literature by arguing that established categories
can evolve. We argue that categories that have an overlapping schema for their
respective labels have the potential to influence each other. We propose that
innovations of one category can drive the evolution of another category through
audience legitimization. We highlight one empirical instance of this by looking at
the influence of western movies produced in Europe on the meaning of the Western
genre in the US.
438
WD18
■ WD17
4 - Towards a Systematic Understanding of How Interest-affiliated
Actors Impact Technology Trajectories
Theodore Khoury, Oregon State University, Bexell 422B, Corvallis,
OR, 97331, United States of America,
ted.khoury@bus.oregonstate.edu, Desiree F. Pacheco
Manufacturing III
Contributed Session
How do specific actors change technology trajectories? Focusing on actors with
specific interest-affiliations that are impactful to innovation paths, we propose how
the strategic actions available to a specific actor’s position can alter the diffusion of
technological innovations over time. We reinforce our proposed theory with clean
energy technology illustrations, and consider various influential actor positions in
both market and non-market roles.
Chair: Zulal Gungor, Prof., Gazi University, Maltepe, Ankara, Turkey,
zulalg@gazi.edu.tr
1 - Total Productive Maintenance Policy Framework and
Implementation of 5s Rules
Bahar Ozyoruk, Assistant Prof.Dr., Gazi University, Faculty of
Egineering, Department of Industrial Engineering Maltepe, Ankara,
06570, Turkey, bahar@gazi.edu.tr
5 - Constrained Clustering for Departmental Reorganization
Christopher Rump, Associate Professor, Bowling Green State
University, Applied Statistics & Operations Research, Bowling Green,
OH, 43403, United States of America, cmrump@bgsu.edu
Total Productive Maintenance (TPM) has attracted the attention of industries all
over the world. Many companies benefit from this policy by increasing the overall
efficiency of machine is trying to use existing capacity more efficiently. In this study,
a firm which produces foam in the process of transition to implement TPM and 5S
implementation of the rules are discussed. The results obtained were presented as
comparatively.
Using data collected from a questionnaire asking how faculty viewed their
connection to other disciplines in the College of Business, we employed an
optimization model to reorganize into fewer departmental clusters in order to rectify
large disparities that have developed over time between departmental faculty sizes.
We compare these results to those found via traditional hierarchical clustering
models as well as ad-hoc groupings proposed by members of the college Faculty
Council.
2 - Multi-objective Decision Making (MODM) Approach in Optimizing
Product Design by the Help of House of Quality: A Case Study
Zulal Gungor, Prof., Gazi University, Maltepe, Ankara, Turkey,
zulalg@gazi.edu.tr, Elif Kilic
In practice, the values of design requirements (DRs) having only a few alternatives
can be discrete in the Quality Function Deployment. We propose a Mixed Integer
Goal Programming (MIGP) formulation to get the optimum solution from a limited
number of DRs alternatives. The solution of MIGP model provides decision makers
with different alternative results by the usage of the lexicographic goal
programming (LGP) approach. The applicability of the proposed models is
demonstrated with a problem.
■ WD16
Managing Product Variety
Contributed Session
Chair: Muge Yayla-Kullu, Asst. Prof., RPI, Lally School of Mgmt., 110 8th
St., Troy, NY, 12180, United States of America, YAYLAH@rpi.edu
1 - Allocating Capacity Among Quality Differentiated Products:
Evidence From Airline Industry
Praowpan Tansitpong, RPI, 110 8th St, Troy,
United States of America, tansip@rpi.edu, Muge Yayla-Kullu
■ WD18
Business Applications
This paper explores how the customer perceived quality and the resource
consumption differences of the products may impact the product line and capacity
allocation decisions of the firms. We empirically investigate the airline industry in
three regions of the world; Asia Pacific, EMEA and North America. We find that
both attributes have a significant impact in all the regions.
Contributed Session
Chair: Alba Bonko, President, Biz Intelligence Solutions, LLC, 9737 NW
41st Street, Miami, FL, 33178, United States of America,
alba_n_nunez@hotmail.com
1 - Work as a Love Object. A New Framework for Analyzing the
Work-self Relation
Brad Almond, Assistant Professor of Management, Texas A&M
University, Division of Business, 1901 S. Clear Creek Rd., Killeen,
TX, 76549, United States of America, brad.almond@ct.tamus.edu
2 - A Unified Framework for Planning a Platform Achieving Both
Strategic and Operational Benefits
Changmuk Kang, Ph.D Student, Seoul National University, 599
Kwanakro, Kwanakgu, Seoul, Korea, Republic of, muk83@snu.ac.kr,
Yoo S. Hong
Building on popular fascination with the idea of “loving what you do,” this paper
explores how work functions as a love object by developing a multi-dimensional
model and testing its structure and relation to key work outcomes using factor
analysis and structural equation modeling. Explores implications for management
and organizations.
Whereas operational benefit of platform sharing, which is reducing differentiation
cost, has been well known, its strategic role of establishing commonly preferred
identity has less been noticed in literature. This study presents a unified framework
for planning a product platform meeting a firm’s strategic goals of both identity
establishment and efficient variety offering. A quality function deployment and
versatility index based approach is applied to identify appropriate platform
components.
2 - Allocation of Bulk Tanks to Customer Sites
Tejinder Pal Singh, Sr. Research Associate, American Air Liquide,
12800 W. Little York Rd, Houston, TX, 770941, United States of
America, tejinder.singh@airliquide.com, Kimberly Ellis
3 - Assortment Planning with Multiple Quality Levels: A Dynamic
Programming Approach
Mark McElreath, Clemson University, 150 Freeman Hall, Clemson,
SC, 29634, United States of America, mmcelre@clemson.edu,
Maria Mayorga
Bulk tank allocation (BTA) problem consists of allocation of tanks to customer sites
for distribution of gases. Distribution is based mainly on Vendor Managed Inventory
(VMI) model. In BTA problem, the goal is to minimize the distribution costs by
having right tank sizes at customer sites. A right tank size at a customer will ensure
that the customer doesn’t run out of the product often and at the same time doesn’t
need deliveries frequently.
The optimal solution to the assortment planning problem with vertical and
horizontal differentiation in which consumer preference is described by a locational
choice model is unknown. We propose a two part solution: a dynamic program to
find the optimal vertical attributes embedded into a line search to find the optimal
horizontal attributes. We compare our approach to metaheuristics, explore the
optimal solution space, and provide insight into the properties of an optimal
assortment.
3 - Optimal Contract Problems in Online Advertising with
Risk Considerations
Md. Tanveer Ahmed, University at Buffalo, SUNY, 333 Bell Hall,
Buffalo, NY, 14260, United States of America,
mtahmed@buffalo.edu, Changhyun Kwon
4 - Product Variety, Out-Of-Stock, and Sales
Xiang Wan, University of Maryland, Van Munching Hall 3354,
College Park, MD, 20742, United States of America,
xwan@rhsmith.umd.edu, Martin Dresner, Philip Evers
In this paper, we study the optimal contract problem for online display
advertisements with pay-per-view pricing scheme. We first provide and analyze a
single contract model, which is shown to be equivalent to the newsvendor problem.
We then consider a stochastic optimization problem with two different contracts and
show that no mixed contract is optimal. However, we show that a mixed strategy
may be optimal when we consider the risk attitude of the publisher.
Product variety has been analyzed by an extensive body of literature. High product
variety stimulates sales, while it raises the difficulty of logistics management and
reduces sales. This paper proposes a framework to investigate the direct and indirect
(through logistics performance) impacts on sales. The results indicate that the
influence of product variety on sales depends on variety in both the degree and
dimensions.
439
WD19
4 - Development of a Global Part Sourcing Optimization Model with
Currency Risk Analysis
Don Zhang, Cost Optimization Analyst, Ford Motor Company, 2101
Village Rd., Dearborn, MI, 48121, United States of America,
xzhang35@ford.com, Mark Everson, Leonardo Vaquero,
Dawn Gontko, David Shepps
get shorter transit times, others longer. Since service levels change, any move
towards dynamic planning should involve pricing and revenue management
considerations. This talk discusses a number of these considerations and gives
guidance to railways looking to make the jump to the next level of planning.
■ WD20
Ford Motor Company operates globally across six continents. Under the “One Ford”
initiative, Ford has been leveraging increased economies of scale. One of these
efforts is to source globally the common parts shared by many vehicle programs. We
have developed a mixed integer programming optimization model and exchange
rate risk assessment methodology to optimize sourcing decisions. We will discuss
our approach for deciding the optimal sourcing decisions and risk assessment for
various scenarios.
Pricing and Revenue Management III
Contributed Session
Chair: Dincer Konur, PhD Candidate, University of Florida,
Industrial and Systems Engineering Department, Gainesville, FL, 32611,
United States of America, dincer@ufl.edu
1 - A Segmentation Study in Applying Revenue Management to the
Hospitality Industry
Murtaza Das, The Rainmaker Group, 5755 North Point Parkway,
Alpharetta, GA, 30022, United States of America,
murtazadas@gmail.com, Renaud Menard
5 - Continuous Improvement and Efficiency Training:
Challenges and Opportunities
Alba Bonko, President, Biz Intelligence Solutions, LLC, 9737 NW
41st Street, Miami, FL, 33178, United States of America,
alba_n_nunez@hotmail.com, Rebeca Lergier, Martha Centeno
We discuss paradigms used in training courses, and highlight some of their strengths
and weakness. Training courses paradigms range from the “recipe” to the
“academic”. The former disregards foundations of the methods, whereas the latter
fails to show practical applications. We propose a scheme that is enterprise-centered,
so that practicing professionals can effectively use quantitative methods, and with
management policies, as part of the continuous improvement cycle of the
enterprise.
Segmentation is a fundamental step in applying revenue management and pricing
which directly impacts forecasting accuracy, and thus revenue optimization. While
forecast accuracy and revenue optimization are paramount to a sound revenue
management strategy, operational limitations should also be considered in the
segmentation analysis. We review the current approaches of segmentation in the
hospitality RM industry, present simulation results, and point out challenges.
2 - A Statistical Methodology to Find Segment Level Parameters using
Aggregate Level Data
Hamed Hasheminia, Sauder School of Business-UBC,
2053 Main Mall, Vancouver, BC, V6Z2T9, Canada,
hamed.hasheminia@sauder.ubc.ca, David Gillen
■ WD19
Practical Applications of Pricing and RM Theory
We develop a novel statistical procedure to estimate segmental demand functions
from aggregate level data. To achieve our result we combine the invaluable
information hidden in integer numbers, characteristics of integer numbers, and use
MLE to estimate parameters at the segment level. The method is applied to estimate
how demands for different segments of passengers (i.e. single passengers, couples,
and so forth) are affected by price, time to the flight, etc.
Sponsored Session
Chair: Scot Hornick, Partner, Oliver Wyman, 155 N. Wacker Drive,
16th Floor, Chicago, IL, 60606, United States of America,
Scot.Hornick@oliverwyman.com
1 - Market-Response-Based Inventory Management for Airlines
and Hotels
James Rider, Associate Partner, Oliver Wyman, 55 Baker Street,
London, W1U 8EW, United Kingdom,
James.Rider@OliverWyman.com, Jessica McLaughlin, Bejugum Rao,
Daniel Sack
3 - Modeling Supplier Wholesale Pricing Decisions with Competitive
Buyers Under Cournot Competition
Dincer Konur, PhD Candidate, University of Florida, Industrial and
Systems Engineering Department, Gainesville, FL, 32611,
United States of America, dincer@ufl.edu, Joseph Geunes
We model a supplier’s wholesale pricing decision for competitive non-identical
buyers as a Stackelberg game. To determine a Stackelberg equilibrium, we first solve
the buyers’ game and analyze the buyers’ quantity decisions under two different
cooperation levels. We then determine the supplier’s optimal wholesale price, and
conduct numerical studies to characterize the value of the information to the
supplier, as well as the effects of buyer and market heterogeneity.
Most of the prevalent seat and room inventory management methods are no longer
adequate to serve the needs of today’s dynamic marketplace. In our novel Market
Response-Based Inventory Management (MRBIM) approach, we generate
recommendations for pricing and availability decisions by taking into account
dynamic marketplace data. Demand is managed more effectively by understanding
customer’s willingness to pay and knowing prevailing competitor prices and
availability. Revenue is maximized by adjusting own fares/rates and availability,
possibly multiple times a day. To facilitate MRBIM implementation, we developed
statistical methods to estimate demand parameters with data that is likely to be
readily available at a typical airline or hotel company. We developed approaches to
interface with current inventory allocation models. Piloting of MRBIM approach at
multiple airlines has revealed consistent revenue benefits.
■ WD22
Service System Development
Sponsored Session
2 - Dynamic Pricing for Aftermarket Auto Parts
Bruce Spear, Associate Partner, Oliver Wyman, 1166 Avenue of the
Americas, New York, NY, 10036, United States of America,
Bruce.Spear@OliverWyman.com, Todd Ebe, Bejugum Rao
We present an application of dynamic pricing at an auto-glass wholesaler. We
estimate customer’s sensitivity to the wholesaler’s price by customer type, part type
and geography. We determine optimal prices that maximize the wholesaler’s
contribution, i.e. revenue minus cost of goods sold, knowing competitors’ prices. We
show the revenue benefits (>4%) due to optimal prices evaluated in a test-control
setting. We discuss data and measurement challenges. Our future efforts will include
extending the approach to retail auto-glass business as well as optimizing part prices
by considering own and competitor inventory levels.
Chair: Ari P.J. Vepsalainen, Professor, Aalto University School of
Economics, Department of Business Technology, P.O. Box 21220,
Helsinki, 00076, Finland, ari.vepsalainen@hse.fi
1 - Functional Selection of Business Processes - Who Works
for the Market?
Ari P.J. Vepsalainen, Professor, Aalto University School of Economics,
Department of Business Technology, P.O. Box 21220, Helsinki,
00076, Finland, ari.vepsalainen@hse.fi, Mika Raulas,
Markku Tinnilä, Jukka Kallio
3 - Revenue Management Concepts for Freight Railways Practicing
Dynamic Routing
Marc Meketon, Oliver Wyman, 212 Carnegie Center, Princeton, NJ,
08540, United States of America, Marc.Meketon@oliverwyman.com,
David Lehlbach
The analysis of the functional needs of different communities and market processes
highlights the full market potential of service development. With extreme functional
specialization, companies and workers will be providing narrower service to
increasing number and variety of market activities and communities. Our case
studies illustrate the working conditions of functional selection and the potential coevolution of private, public and commercial institutions.
Most railways world-wide operate on a fixed scheduling plan that allows only one
route per railcar. However, as railways begin to plan their next generation of carscheduling systems, they should consider the possibility of dynamic train scheduling
that changes the operating plan and the rules for routing cars dynamically. As a
simple example, when faced with capacity limitations in a certain corridor, it may
make sense to divert some cars to an alternate route. While dynamic planning could
increase efficiencies, it could also change customer service. Some customers could
440
WD24
2 - Dynamic Policies in Knowledge-Based Service System with
Feedback Information
Qifeng Shao, Northwestern University, 2145 Sheridan RD, IEMS
C210, Evanston, IL, 60208, United States of America,
qshao@northwestern.edu, Seyed Iravani
■ WD24
We propose a modeling framework of a knowledge based service system with an
information feedback mechanism. The feedback system provides information
regards correctness of the agent’s decisions. With help from the feedback system, the
agent adjusts processing strategies to deal with information crises that can change
the state of arrival customers. Besides the optimal strategy, we examined several
heuristics and found one effective policy with a simple threshold design.
Sponsor: Public Programs, Service and Needs/ Transportation
Science and Logistics Society
Sponsored Session
Joint Session SPPSN/ TSL: Decision Support for
Emergency Response and Public Safety
Chair: Alex Savachkin, Assistant Professor, University of South Florida,
4202 E. Fowler Avenue ENB 118, Tampa, FL, 33620, United States of
America, alexs@usf.edu
1 - Non-Pharmaceutical Interventions (NPI) for the Mitigation of
Pandemic Influenza
Dayna Martinez, Doctoral student, University of South Florida,
Tampa, FL, 33620, United States of America, dlmartin@mail.usf.edu,
Tapas K. Das, Alex Savachkin
3 - A Simulation Based Framework for Service Facility Internal
Layout Design
Ming Xie, IBM Research - China, Diamond Building, ZGC Software
Park, Beijing, China, xieming@cn.ibm.com, Jinyan Shao, Bin Zhang,
Wenjun Yin, Jin Dong
Service facilities, including bank branches, supermarkets, etc. are closely related to
our lives. Whereas, it is a difficult task to make decisions on how to design internal
layout and configuration for them. In this paper, we propose a service facility
internal layout optimization framework as well as how to model the system into a
multi-agent system. Then, a bank branch scenario from real world is adopted to
demonstrate the methodology and implementation.
In the event of an influenza pandemic, non-pharmaceutical interventions (NPI),
such as social distancing, will likely be the only effective containment measure
available in the early phase of the pandemic. In this research, we examine various
NPI strategies, such as quarantine of isolated cases, household quarantine, school
and workplace closures, and study their effect on the infection attack rate and the
societal and economic cost of the pandemic.
2 - Developing an Agent-based Model for Poliovirus Transmissions for
Post-eradication Outbreak Response
Hazhir Rahmandad, Assistant Professor, Virginia Tech, 7054 Haycock
Rd., room 430, falls church, va, 22043, United States of America,
hazhir@vt.edu, Kimberly Thompson, Radboud Duintjer-Tebbens,
Kun Hu
■ WD23
Retail Managment
Contributed Session
Chair: Mahesh Kumar, Assistant Professor, R.H. Smith School of Business,
University of Maryland, 4321 Van Munching Hall, College Park, MD,
20742, United States of America, kumarmahesh@gmail.com
1 - Assortment Planning of Configurable Products
Edward Umpfenbach, PhD Student, Wayne State University,
20011 12 Mile, Roseville, MI, 48066, United States of America,
as6964@wayne.edu, Alper Murat, Ratna Babu Chinnam
Given the possibility of reintroductions of live polioviruses into communities after
eradication, designing effective and efficient responses to potential outbreaks is
necessary. In this study we develop an individual-based simulation model of
poliovirus transmission dynamics in a population and use this model the explore
alternative response strategies. We also explore the importance of different
assumptions with regard to human contact network and transmission mechanisms.
Considerable work has been done to optimize the assortments of high sales density
products. We introduce a method to estimate demand and substitution parameters
of a configurable product given sales data, then solve a joint supply chain planning
and assortment planning problem.
3 - Agent-based Simulation of Mass Egress From Large Public Events:
Current State and Next Steps
Douglas A. Samuelson, President and Chief Scientist, InfoLogix, Inc.,
Annandale, VA, United States of America,
samuelsondoug@yahoo.com
2 - The Impact of Execution Errors on Inventory Record Inaccuracy and
Retail Out-Of-Stock
Howard Hao-Chun Chuang, Doctoral Student, Mays Business
School, Texas A&M University, Wehner 301C - TAMU 4217,
hchuang@mays.tamu.edu, Rogelio Oliva
We review a variety of recent work on agent-based simulation of mass egress,
especially from sports arenas, noting the capabilities, limitations and design
compromises in some of the most interesting models. We then discuss next steps,
including modeling group movement, movement by emergency responders,
placement of treatment centers, effects of toxic air- and water-borne plumes, and
integration of planning and training models with real-time crisis management
information systems.
We model a continuous (Q,R) inventory system and analyze the impact of
execution errors on inventory record inaccuracy and retail out of stock. The
existence of multiple errors could disrupt ordering decisions and reduce on-shelf
availability. We formalize the argument analytically and develop a system dynamics
model. We perform Monte-Carlo sensitivity simulation to identify the most costly
execution errors. Then we provide suggestions to improve operational accuracy
within a retail store.
4 - Decision Support Systems for Pandemic Influenza (PI) Surveillance
Alfredo Santana-Reynoso, PhD Candidate, University of South
Florida, 4202 E. Fowler Avenue ENB118, Tampa, FL, 33620,
United States of America, asantan2@mail.usf.edu, Diana Prieto,
Alex Savachkin, Sharad Malavade
PI contingency plans have concentrated their efforts into a new virus strain of low
transmissibility and high severity originated in SE Asia. The H1N1 2009 outbreak
featured higher transmissibility and lower severity than expected, and was
originated in North America. This presentation analyzes how these scenarios have
been managed by the current PI surveillance systems. Robust multi-epoch decision
support systems for PI surveillance adaptable to a more diverse range of situations
are presented.
3 - A Pooling Procedure to Improve Sales Forecasts for Retail Fashion
Goods with Limited Past Sales Data
Mahesh Kumar, Assistant Professor, R.H. Smith School of Business,
University of Maryland, 4321 Van Munching Hall, College Park, MD,
20742, United States of America, kumarmahesh@gmail.com
Most sales forecasting methods are likely to perform poorly if only a small amount
of past sales data is available for analysis. The situation is common for new fashion
items in a store, especially during the early weeks of a selling season. We overcome
this limitation of a forecasting method by pooling data from groups of similar items
using a two-step clustering procedure. The new procedure is flexible to use and is
computationally fast. Its effectiveness is demonstrated on a real-world data.
441
WD25
■ WD25
2 - Reliable Networks That Can be Modeled by Graphs with Edge
Connectivity Equal to Two
Leandro Teixeira, Centro de Anàlises de Sistemas Navais, Praça Barao
de Ladàrio, AMRJ , Centro, rio de janeiro, RJ, 20091-000, Brazil,
leandrodteixeira@yahoo.com.br, Nair Abreu, Leonardo Lima
Transportation, Planning III
Contributed Session
Deterministic and probabilistic parameters can be used to measure the reliability of a
graph that models a network. Consider that each node of the network is reliable
and its failure is related to the probabilities of the edge failures of the graph when
these probabilities occur randomly and independently. In this work, a class of graphs
with maximum reliability among all graphs with edge connectivity equal to two is
presented.
Chair: Wei Fan, Assistant Professor, The University of Texas at Tyler,
Department of Civil Engineering, 3900 University Blvd., Tyler, TX, 75799,
United States of America, wfan@uttyler.edu
1 - Expansion Planning of Road Networks via
Agent-Based Optimization
Alireza Kabirian, University of Alaska - Anchorage, Rasmuson Hall,
Suite 318D, 3211 Providence Dr, Anchorage, AK, 99508,
United States of America, a_kabirian@yahoo.com
3 - An Efficient Algorithm for the Distributed Data Retrieval Problem
Alex Sprintson, Assistant Professor, Texas A&M University, TAMU
3128, College Station, 77843, United States of America,
spalex@tamu.edu, Zakia Asad, Mohammad Asad R Chaudhry
We develop optimization models and methodologies for expansion planning of an
existing network of roads over a long-run horizon. Specifically, we aim at
determining where and when new roads should be constructed and which and
when old roads should be reconstructed to minimize public construction costs as
well as travelers’ expenses. This decision support model helps transportation
managers in public sector make comprehensive and data-driven decisions about
expansion of road infrastructures.
We consider the problem of accessing large volumes of data stored on multiple
locations across a storage network. We assume that data is stored in either original
or encoded form on multiple servers across the network. Our goal is to find a set of
disjoint paths of minimum total cost that connect the client with some of the servers
across the network such that client is able to retrieve the required data. We present
an efficient polynomial-time algorithm for this problem.
2 - The Changes in Users’ Perceptions on Transportation Problems in
the Last 10 Years
Xiaoyu Zhu, PhD Candidate, University of Florida, 365 Weil Hall,
P.O. Box 116580, Gainesville, FL, 32611, United States of America,
shuxy03@ufl.edu
4 - An Efficient Heuristic Algorithm for Minimum Labeling Spanning
Tree Problem
Kaveh Farokhi Sadabadi, Faculty Research Assistant, University of
Maryland, ENCE Department, 1173 Glenn L. Martin Hall, College
Park, MD, 20742, United States of America, kfarokhi@umd.edu,
Ali Haghani
To improve the transportation system, it is important to understand the travelers’
perceptions about transportation issues to assess user acceptance of the policies.
With developments in transportation, the perceptions might change greatly in the
last decade. To understand the people’s perceptions about the most important
transportation issue will provide more information for value the project efficiency
and public acceptance.
We propose a heuristic algorithm to solve Generalized Minimum Labeling Spanning
Tree problem. This is an NP hard problem with applications in telecommunications
and network design. Many algorithms are proposed to solve GMLST. Maximum
Vertex Covering (MVCA) and Genetic Algorithm (GA) are well-known. Global
optimality of these methods is not guaranteed, nor are they efficient to deal with
large problems. Reported examples show the efficiency and quality of the proposed
method compared to others.
3 - A Sensor-based Vehicle Routing Problem Algorithm
Chrysafis Vogiatzis, University of Florida, Weil 303, Gainesville, FL,
32611, United States of America, chvogiat@ufl.edu, Panos Pardalos
Vehicle routing has always been a vital problem for transportation and traffic
congestion. Throughout the years, solutions have been proposed but are usually
hard to implement because of the continuous time nature of the problem, which
cause alterations in conditions and constraints. We propose an online algorithm
which searches for an optimal solution based on the input provided by vehicle to
vehicle sensor communication using augmented lagrange relaxation.
■ WD28
Computer Models: Prediction and Calibration
Sponsored Session
4 - Optimal Toll Design with Uncertain Demand
Wei Fan, Assistant Professor, The University of Texas at Tyler,
Department of Civil Engineering, 3900 University Blvd., Tyler, TX,
75799, United States of America, wfan@uttyler.edu
Chair: Lulu Kang, Assistant Professor, Illinois Institute of Technology,
Engineering 1 Building, Applied Math, 10 West 32nd Street, Chicago, IL,
60616, United States of America
1 - Model Calibration with Minimal Adjustments
Chia-Jung Chang, PhD Student, Georgia Institute of Technology,
755 Ferst Drive, Atlanta, GA, United States of America,
cchang43@gatech.edu, Roshan Vengazhiyil
An optimal toll design problem (OTDP) under a second-best link based congestion
pricing scheme is discussed in this presentation, in which the selection of both toll
locations and toll levels needs to be optimally determined with uncertain demand. A
bi-level optimization model is formulated and a simulation-based genetic algorithm
procedure is proposed to solving the OTDP. Numerical results are presented and
future research directions are also given.
Model calibration refers to estimating unknown parameters in a physics-based
model from real data. When model assumption is violated, the estimates become
inaccurate leading to poor model prediction. Besides, all works ignore the
potentially important bias that can occur in the observations. In this work, we
develop a methodology for calibrating the physical model in the presence of both
model and experimental biases. Two real case studies are presented to demonstrate
the prediction ability.
■ WD27
Networks and Graphs
2 - Improving Prediction by Integrating Analytical Models with Finite
Element Models
Shan Ba, Georgia Institue of Technology, 765 Ferst Drive, NW,
Atlanta, GA, 30332, United States of America, shan.ba@gatech.edu,
Roshan Vengazhiyil, Ramesh Singh
Contributed Session
Chair: Alex Sprintson, Assistant Professor, Texas A&M University, TAMU
3128, College Station, 77843, United States of America, spalex@tamu.edu
1 - Screen Sizes of Paths
Anthony Harrison, Texas State University, 601 University Drive,
San Marcos, United States of America, ah1411@txstate.edu,
Nathaniel Dean
For the micro grooving process, we develop an innovative two-step design of
experiments approach to efficiently extract information from both the simple
analytical force model and the complex finite element model. The simple but less
accurate analytical model can be adjusted by data from the time-consuming finite
element simulations, and finally forms an effective surrogate micromachining
cutting model which is fast, accurate and economically viable to use.
Sphere of infuence graphs (SIGs) are a representation of spatial relationships
between points. They can be useful in areas related to pattern matching. We
consider a graph invariant for SIGS called the screen size. This is the smallest integer
k such that a given SIG can be realized on a k by k grid. We find the screen size for
paths and then explore integer programming formulations for the problem and
explain some of the difficulties encountered with this approach.
3 - Kernel Sum Regression and Interpolation
Lulu Kang, Georgia Institute of Technology, Atlanta, GA, 30332,
United States of America, lkang@isye.gatech.edu,
Roshan Vengazhiyil
In this paper, we propose a new nonparametric regression method, called kernel
sum regression method. It utilizes iterative kernel regression to achieve better
prediction accuracy. Meanwhile, if the the number of kernel regression goes to
infinity, the kernel sum regression becomes an interpolation method. We also
investigated some properties of the kernel sum regression and interpolation
methods, and provide algorithm to estimate the bandwidth parameters.
442
■ WD29
WD31
3 - Analysis Methods for Non-regular Fractional Factorial Designs
Shilpa Shinde, Arizona State University, 1249 E Spence Avenue
Apt#343, tempe, AZ, 85281, United States of America,
scvmadha@asu.edu, Douglas Montgomery
Quality Improvement in Complex Systems
Non-regular designs are very effective alternatives to regular fractional factorials.
Their use is restricted due to the lack of robust analysis techniques. We present a
new analysis and variable selection technique which will help identify significant
effects in a non-regular design.
Sponsored Session
Chair: Ran Jin, Georgia Institute of Technology, 755 Ferst Dr. NW,
Atlanta, United States of America, jinr@gatech.edu
1 - Challenges of using Feature Selection Methods for
Waveform Signals
Nasim Arbabzadeh, Rutgers University, 23667 BPO WAY, Piscataway,
NJ, 08854, United States of America, nasim@eden.rutgers.edu,
Susan Albin
4 - Exact Inference for Progressively Type-I Censored Exponential
Failure Data
David Han, Assistant Professor, University of Texas at San Antonio,
One UTSA Circle, San Antonio, TX, 78249, United States of America,
david.han@utsa.edu, N. Balakrishnan, G. Iliopoulos
Progressively Type-I censored life-test is discussed under the assumption of
exponential distribution. For small sample sizes, a practical modification is proposed
to guarantee a feasible test under this scheme. We then obtain the exact sampling
distribution of the MLE of the mean parameter under the condition ensuring its
existence. Using the exact method as well as the asymptotic and bootstrap methods,
we then discuss construction of confidence intervals and their performance via
simulations.
Recent technological advances in data capture and processing result in highdimensional waveform signals, making the analysis difficult for the process
engineers. Feature selection methods can be used to reduce the features to a
manageable number. In this paper, different feature selection methods have been
compared on several real datasets, including NIR spectra and vertical depth profile,
and the impact of different sampling frequencies on their performances has been
investigated.
2 - Generalized Selective Assembly
Matthias H Tan, Student, Jeff Wu/ Department of Industrial &
Systems Engineering, Georgia Institute of Technology, 301 10th
Street NW, Apt 208A, Atlanta, GA, 30318, United States of America,
mtan6@gatech.edu, Jeff Wu
■ WD31
Quality Management I
This paper develops a generalized version of selective assembly, called GSA, for
improving the quality of assemblies of single units of different component types.
Two variants are considered: direct selective assembly, which uses measurements on
component characteristics, and fixed bin selective assembly, which only requires
sorting components into bins. We formulate the problem of matching N components
of each type to give N assemblies that minimize quality cost as linear integer
programs.
Contributed Session
Chair: Karl Majeske, Associate Professor of Quantitative Methods
Management, Oakland University, School of Business Administration,
Rochester, MI, 48309, United States of America, majeske2@oakland.edu
1 - CUSUM Control Charts for Respiratory Syndromic Surveillance
Huifen Chen, Professor, Chung-Yuan University, Department of
Industrial and Systems Eng., Chung-Yuan University, Chungli, 320,
Taiwan - ROC, huifen@cycu.edu.tw, Chaosian Huang
3 - Relationship Between Seamless Tube Quality and Piercing
Vibration Data
Weidong Zhang, Vice Director and Associate Professor, National
Cecter for Materials Service Safety,University of Science and
Technology Beijing, 30 Xueyuan Road, Haidian District, Beijing,
100083, China, zwd@ustb.edu.cn, Ran Jin, Jianjun Shi
This work applies CUSUM charts for detecting outbreaks of the respiratory
syndrome. The data, daily ambulatory-care visits based on population of size 160
thousand, are from Taiwan National Health Insurance Research Database. We
construct a standardized CUSUM chart based on residuals of a fitted regression
model with an ARMA error term using the 2005 and 2006 data. The CUSUM chart
seems to be able to detect aberrations of respiratory syndrome when used to
monitor the 2007 and 2008 data.
We can get vibration data of seamless tube piercing by two cameras. There may be
some relationship between quality of seamless tube and vibration data. We can find
the relationship by system informatics method.
2 - An Integrated Approach for Multivariate Process Control in
Automobile Manufacturing
Xiaoyu Ma, PhD Student, Industrial&manufacturing engineering
department, wayne state university, 4815 4th Street, detroit, MI,
48202, United States of America, eb1946@wayne.edu, Alper Murat,
Kai Yang, Adel Alaeddini
■ WD30
Statistics/Quality Control III
Increasing availability of multivariate process data demands us to develop effective
analysis techniques. We developed a comprehensive approach that uses statistical
and optimization techniques. It performs abnormal signal detection, influential
features selection in optimized fashion during multivariate statistical control
practice. This approach can help root cause analysis in automobile manufacturing
process and examples with real data are presented.
Contributed Session
Chair: David Han, Assistant Professor, University of Texas at San Antonio,
One UTSA Circle, San Antonio, TX, 78249, United States of America,
david.han@utsa.edu
1 - A Variable Sampling Hotelling T2 Chart for Monitoring Simple Linear
Quality Profiles
Galal Abdella, PhD Student, Wayne State University, 4815 4th Street,
Detroit, MI, 48202, United States of America, bb2941@wayne.edu,
Kai Yang, Adel Alaeddini
3 - Sustaining Quality Performance Through Collective Mindfulness
Hung-Chung Su, Student, University of Minnesota, 3-150 321-19th
Avenue South, Minneapolis, MN, 55455, United States of America,
suxxx051@umn.edu, Kevin Linderman
Organizational mindfulness is an emerging construct that has not receive enough
attention in the quality management. We provide evidence of the five dimensions of
organizational mindfulness and examine its impact on innovation, improvement
and the reliability of quality performance. We discuss the implications for sustaining
quality performance and possible contributions to the organizational learning and
dynamic capability literature.
We design a variable sampling T2 scheme to enhance the detecting speed of offtarget conditions while keeping the total number of samples low. We constructed an
optimization model solved by using the genetic algorithm. The performance of the
proposed scheme is compared with its fixed sampling counterparts under different
conditions.
2 - Beta Model-based Control Chart for Fraction Monitoring
Carla ten Caten, Profa. PhD., PPGEP/UFRGS, Av. Osvaldo Aranha,
99 - 5° andar, Porto Alegre, RS, 90.035-190, Brazil,
tencaten@producao.ufrgs.br, Angelo Sant’Anna, Michel Anzanello
4 - Dynamic Part Fitting to Improve Automotive Body Quality
Karl Majeske, Associate Professor of Quantitative Methods
Management, Oakland University, School of Business
Administration, Rochester, MI, 48309, United States of America,
majeske2@oakland.edu
Modelo-based control charts often use multiple regression models. We propose a
Beta model-based control chart (BMCC) for monitoring fraction that varies with the
adjustment of control variables. The BMCC monitors deviances on Beta model’s
residuals. We use sensitivity analysis to compared BMCC with Hawkins (1991) and
Haworth’s(1996) methods.
The gaps and flushness between assemblies, such as door-to-fender, represent a
highly visible automotive body quality characteristic. Traditional design and
assembly methods attach a door to the body by bolting hinges into established
mounts. This technique uses vision system data to orient parts during final assembly
to optimize quality.
443
WD33
■ WD33
■ WD35
Optimization Models in Data Mining with Applications
in Biomedicine
Ranking and Internet Applications
Sponsored Session
Sponsored Session
Chair: Mariana Olvera, Columbia University, 500 W. 120th Street,
Mudd Building, Room 306, New York, NY, 10027,
United States of America, molvera@ieor.columbia.edu
1 - User Selection Process for More Profitable Display Advertising
Ana Radovanovic, Research Scientist, Google Research,
76 Ninth Ave., New York, NY, 10011, United States of America,
anaradovanovic@google.com
Chair: Petros Xanthopoulos, University of Florida, 303 Weil Hall,
P.O. Box 116595, Gainesville, FL, 32611, United States of America,
petros.xanthopoulos@gmail.com
1 - Early Detection of Cardiovascular Disease
Tsung-Lin Wu, tlwu@isye.gatech.edu, Eva Lee
Cardiovascular diseases are the No 1 cause of death in US. Coronary heart disease is
caused by atherosclerosis, the narrowing of the coronary arteries due to fatty build
ups of plaque, producing angina pectoris, heart attack or both. We present novel
early detection based on classification of traditional risk factors and novel
biomarkers. The results can detect risk conditions of arteries and allow clinicians to
perform early intervention. This work is joint with cardiologists at Emory U.
One of the key performance objectives in display advertising business is maximizing
the proportion of user clicks out of all of the shown ads by a given advertiser.
However, the click probability significantly depends on users we are showing a
certain ad to. We introduce a self-organizing online policy for updating user
members’ lists and show that this policy allows us to achieve nearly optimal longterm proportion of clicks out of all online inventory that is handled by a publisher.
2 - Robust Data Mining with Application in Biomedicine
and Engineering
Petros Xanthopoulos, University of Florida, 303 Weil Hall, P.O. Box
116595, Gainesville, FL, 32611, United States of America,
petros.xanthopoulos@gmail.com, Panos Pardalos, Mario Guarracino
2 - Implicit Renewal Theory for Ranking Algorithms
Mariana Olvera, Columbia University, 500 W. 120th Street,
Mudd Building, Room 306, New York, NY, 10027,
United States of America, molvera@ieor.columbia.edu,
Predrag Jelenkovic
Supervised and unsupervised learning under uncertainty has become a very
important problem in data analysis. In this talk we present some algorithms based
on robust optimization for addressing data uncertainty issues.
We present a stochastic framework to analyze the qualitative large scale behavior of
a family of ranking algorithms, in the same spirit of Google’s PageRank algorithm,
via implicit renewal theory. Our analysis is based on a stochastic recursion
constructed on a tree, and the techniques we develop can be applied to both linear
and non-linear recursions. We extend prior work to allow a general correlation
structure among the different inputs of the algorithm.
3 - Rule Extraction From Support Vector Machines and Applications to
Medical Diagnosis
Sara Nourazari, University of Oklahoma, 100 East Boyd, SEC T 301,
Norman, OK, 73019, United States of America, sara.n@ou.edu,
Theodore Trafalis
■ WD36
Among the classification methods, the propositional if-then rules are very popular
providing a transparent classification decision. In the case of high-dimensional data,
SVMs often perform significantly better but suffer from incomprehensibility. In this
work we evaluate different techniques to extract expressive rules from SVMs and
apply those in real life cases such as medical diagnosis.
Quality Management II
Contributed Session
4 - Network Based Models for Analysis of SNPs
Zeynep Ertem, Texas A&M University, 1313 Zachry, College Station,
TX, 77840, United States of America, zeynepsertem@gmail.com,
Sergiy Butenko
Chair: Scott Dellana, Associate Professor, East Carolina University, Bate
3102, Dept of Marketing & Supply Chain Mgmt, Greenville, NC, 27858,
United States of America, dellanas@ecu.edu
1 - A Robust Technique to Process Qualitative Customer Data and
Build Satisfaction Models
Jose Luis Ribeiro, Dr., UFRGS, Av. Osvaldo Aranha 99,
Porto Alegre, RS, 90035-190, Brazil, ribeiro@producao.ufrgs.br,
Maria Auxiliado Tinoco
Constructing associated graph-theoretic models becomes more important as
communicating vast amount of information accumulated in the laboratories each
day is getting harder. Single Nucleotide Polymorphisms (SNPs) are of paramount
importance in DNA related studies due to their role in variation of species. In this
talk, we first survey metwork based models arising in computational biology and
then concentrate on applications of cluster-detection algorithms to analyze SNP
data.
Customer survey may be used to collect qualitative data and build satisfaction
models. However, due to respondents’ lack of engagement, customer survey is
usually contaminated with noise. Following robust regression principles, we
developed a technique to process qualitative data according to its consistence,
supporting the construction of robust satisfaction models.
5 - Parametric Support Vector Machines
Altannar Chinchuluun, Dr, Centre for Process Systems Engineering,
Imperial College London, London, United Kingdom,
a.chinchuluun@imperial.ac.uk, Ashwin Arulselvan,
Stratos Pistikopoulos
2 - Supply Chain Quality Management Practices and Perceptions:
A Preliminary Empirical Study
Scott Dellana, Associate Professor, East Carolina University, Bate
3102, Dept of Marketing & Supply Chain Mgmt, Greenville, NC,
27858, United States of America, dellanas@ecu.edu, John Kros
Support vector machines have been extensively studied and used in practice as a
data mining tool especially in the field of biomedicine. We study the parametric
support vector machine, where in we introduce the degree of misclassication as the
parameter. Multiparametric prorgamming techniques are used for the resulting
multiparametric mixed integer programs.
Recent global supply quality problems have underscored the need for a better
understanding of quality across the supply chain. Studies in supply chain quality are
few, limited, and with mixed results warranting more extensive study. We examine
quality management practice by industry class and supply chain organizational
position and compare agreement between perceived supplier quality management
practices reported by customers and quality practices reported by their supplier
groups.
444
■ WD37
■ WD38
Stochastic Processes
Algorithms for Real-Time Equilibrium and
Relocation Problems
Contributed Session
WD39
(Joint Cluster ICS)
Sponsored Session
Chair: Tianke Feng, Industrial and Systems Engineering, University of
Florida, 303 Weil Hall, P.O. Box 116595, University of Florida,
Gainesville, FL, 32611, United States of America, fengtk@ufl.edu
1 - Sharp Bounds for the Distribution of Critical-path Length
Munevver Mine Subasi, Assistant Professor, Florida Institute of
Technology, 150 W. University Blvd, Melbourne, FL, 32901, United
States of America, msubasi@fit.edu, Ersoy Subasi, Andras Prekopa
Chair: Miguel F. Anjos, University of Waterloo, 200 University Avenue
West, Waterloo, ON, Canada, anjos@stanfordalumni.org
1 - Parametric Complementarity Problems for Online Optimal Control
Mihai Anitescu, Computational Mathematician, Argonne National
Laboratory, Math and Computer Science Division, 9700 S Cass Ave,
Argonne, IL, 60439, United States of America, anitescu@mcs.anl.gov,
Victor Zavala
In PERT we are frequently concerned with the problem to estimate the values of the
probability distribution or expectation of the critical-path length. We develop a
bounding technique to obtain sharp bounds for the values of the distribution of the
critical-path length under moment information and the assumption that the random
length of each arc follows a beta distribution.
We demonstrate that if points along the solution manifold of a nonlinear model
predictive control problem are consistently strongly regular, it is possible to track the
manifold approximately by solving a single linear complementarity problem (LCP)
at each control step. We derive a fast, augmented Lagrangean tracking algorithm
and demonstrate the developments through a numerical case study.
2 - Evolutionary Computation-based Statistical Estimation Models for
Complex System Analysis Based on Count Data
Emily Zechman, Assistant Professor, Texas A&M University, 3136
TAMU, College Station, TX, 77843, United States of America,
ezechman@tamu.edu, Seth Guikema, Royce Francis
2 - Real-time Optimization and Differential Variational Inequalities
Victor Zavala, Argonne National Laboratory, Math and Comp.
Science Div., Bdg 240, 9700 S Cass Ave, Argonne, IL, 60439,
United States of America, vzavala@mcs.anl.gov, Mihai Anitescu
Count data is ubiquitous in engineering practice, and forecasting future counts of
events based on past data is a critical problem. Examples include forecasting power
outages and estimating the risk of traffic accidents. This research will explore
flexible, data-adaptive regression models for count data that preserve insights into
system behavior while allowing exploration of new combinations of model
structures. A new evolutionary computation-based method will be developed and
demonstrated.
We present new insights into how to achieve higher frequencies in real-time
optimization. The basic idea is that, instead of solving a full NLP problem at each
sampling time, we solve a single, truncated QP problem. We prove that this
corresponds to a time-stepping scheme applied to a differential variational
inequality. We propose a fast and stable scheme using augmented Lagrangian
regularization and projected Gauss-Seidel to track the solution manifold.
3 - The Replacement Problem in Manufacturing Stochastic Systems
Eva Selene Hernàndez Gress, PhD, Universidad Autónoma del
Estado de Hidalgo, Abasolo 600 Col. Centro, Pachuca, 42000,
Mexico, evah@uaeh.edu.mx
3 - A Stochastic Optimization Model for Ambulance Relocation
Joe Naoum-Sawaya, University of Waterloo, 200 University Av W,
Waterloo, Canada, jnaoumsa@engmail.uwaterloo.ca, Samir Elhedhli
The Replacement Problem is modeled with Linear and Dynamic Programming. This
problem can be modeled also as a finite, irreducible, homogeneous Markov Chain.
The transition probabilities matrix and the optimal basis associated to the Linear
Programming model are perturbed to find regions of feasibility and optimality. Some
perturbations bounds of the transition probabilities are explored and a perturbation
bound for the optimal basis is also proposed.
In this talk, we present our recent work on implementing a real time ambulance
relocation system for the Region of Waterloo Emergency Medical Services. We
formulate a stochastic optimization model and devise a heuristic that finds good
solutions quickly. Results using the Region of Waterloo EMS data are presented.
4 - Markov Decision Processes with Uncertain Rewards
Chin Hon Tan, PhD Student, Department of ISE, University of
Florida, 303 Weil, University of Florida, Gainesville, FL, 32611,
United States of America, chinhon@ufl.edu, Joseph Hartman
■ WD39
Algorithms and Applications for Integer Programming
Sequential decision problems can often be modeled as Markov decision processes.
Classical solution approaches assume that the parameters of the model are known.
However, the rewards are often estimated and uncertain in practice. In this paper,
we look at the marginal change in the value function as a result of the error in the
reward estimate and identify the region in which a policy remains optimal. We
illustrate this work with a stochastic lot-sizing problem.
Sponsored Session
Chair: Yongpei Guan, University of Florida, 303 Weil Hall, Gainesville, FL
United States of America, guan@ise.ufl.edu
1 - Fast Algorithms for Special Cases of the Minimum Cost
Flow Problem
Bala Vaidyanathan, Operations Research Advisor, FedEx Express,
3680 Hacks Cross Road, Memphis, TN, 38125, United States of
America, bala.vaidyanathan@gmail.com
5 - Sequential Stochastic Assignment Problem with
Postponing Decisions
Tianke Feng, Industrial and Systems Engineering, University of
Florida, 303 Weil Hall, P.O. Box 116595, University of Florida,
Gainesville, FL, 32611, United States of America, fengtk@ufl.edu,
Joseph Hartman
We consider special cases of the minimum cost flow problem when the nodes lie on
a line, a circle, or a tree. We show that the properties of these problems can be
exploited to develop specialized algorithms that run significantly faster than
minimum cost flow algorithms for general networks. These problems find
applications in areas such as transportation, electric power transmission, production
planning, telecommunications, computational biology, and computational music.
The sequential stochastic assignment problem has wide applications in
abandonment problems and health care management, and has been well studied. It
assumes that jobs arrive randomly with random values. Upon arrival, a job’s value is
known and the decision maker immediately decides whether to accept or reject it.
In this research, we study the value of postponing decisions by allowing a decision
maker to hold jobs. We analyze the optimal threshold policies for this version of the
problem.
2 - Polyhedral Results for MIPs with Cardinality Constraints
Ilksen Icyuz, University of Florida, 303 Weil Hall, Gainesville, 32611,
United States of America, eceicyuz@ufl.edu, Jean-Philippe Richard
We consider several mixed integer programs arising from applications that contain
various forms of cardinality constraints. For these models, we review existing
polyhedral results and obtain new strong valid inequalities based on disjunctive and
lifting techniques. We also characterize situations in which these inequalities are
sufficient to completely define the associated convex hulls. Finally, we present the
results of a computational study aimed at testing the strength of these new cuts.
445
WD40
3 - Strong Formulations for Lot-Sizing Problems with Disruptions
Zhili Zhou, University of Florida, 303 Weil Hall, Gainesville, FL,
32611, United States of America, zlzhou@ufl.edu, Yongpei Guan
■ WD41
Most previous research on lot-sizing problems assumed no disruptions. However,
disruptions occur in practice, which lead to extra outsourcing or production costs, as
compared to the normally scheduled case. We formulate this problem as a robust
integer program, and derive facet-defining inequalities for the problem. Final
computational experiments show the effectiveness of our proposed approach.
Metaheuristics II
Contributed Session
Chair: Fan Wang, Prof., Sun Yat-sen Business School, Sun Yat-sen
fanwang@gmail.com
1 - A Modified Particle Swarm Optimization Algorithm
Junhyuk Park, Pohang University of Science and Technology,
Nam-Gu, Hyoja-Dong, POSTECH Eng 4-207, Pohang, Korea,
Republic of, sacarlee@postech.ac.kr, Byung-In Kim, Jongsung Lee
4 - New Cutting Planes for Cardinality Optimization
Ismael De Farias, Texas Tech University, Lubbock, TX, United States
of America, ismael.de-farias@ttu.edu, Ming Zhao, Rajat Gupta,
Ernee Kozyreff
We study the cardinality optimization polytope and extensions, particularly the set
of the minimum 0-norm optimization problem. We present new cutting planes for
them and computational results on their use in branch-and-cut.
In classical PSO algorithms, the global best solution has a strong influence on the
entire population. As a result, particles may rapidly converge to a premature global
best solution without exploring enough search space. In this presentation, we
extend the searching capability of particles by limiting the influence of global best
solution. We compare the performance of the algorithm with several existing
algorithms.
■ WD40
2 - A Genetic Algorithm for the Team Formation Problem
Paul Rubin, Michigan State University, The Eli Broad Graduate
School of Managem, Michigan State University, East Lansing, MI,
48824, United States of America, rubin@msu.edu, Lihui Bai
Robust Optimization
Contributed Session
Chair: Bacel Maddah, Assistant Professor, American University of Beirut,
P.O. Box 11-0236 Riad El Solh, Beirut, 1107-2020, Lebanon,
bm05@aub.edu.lb
1 - Handling Uncertainty in Supplier Selection using
Robust Optimization
Sheela Siddappa, Technical Architect, Infosys Technologies Limited,
Electronic City, Bangalore, India, sheela_siddappa@infosys.com,
Paresh Kumar Marwaha
We consider the team formation problem that assigns individuals with various
values of attributes to teams so that the differences across teams with respect to
each attribute are minimal. The problem is formulated as a mixed integer linear
program and solved by a genetic algorithm with a constraint programming solver.
Numerical results on randomly generated as well as real problems are reported.
3 - Exploration of a Functional Programming Approach for
Developing a Metaheuristic
Dennis Drinka, Exploration of a Functional Programming Approach
for Developing a Metaheuristic, University of Alaska Anchorage,
3211 Providence Drive, Anchorage, AK, 99508,
United States of America, afded@uaa.alaska.edu
Selecting the right set of suppliers to procure items can help reduce company’s
expense and improve customer satisfaction. This research tries to account for
uncertainty in supplier’s performance, capacity, and cost while selecting the
suppliers. We develop a two step process 1) select suppliers based on the uncertainty
in their performance 2) estimate procurement quantity from each supplier based on
the uncertainty in supplier’s capacity, cost, etc. A Robust Optimization methodology
is adopted.
This presentation explores the use of a functional programming approach to drive a
metaheuristic for solving a combinatorial optimization problem. In particular, it
explores the use of LINQ to Objects to implement a tabu search procedure. It will
demonstrate the use of this approach on the All Units Quantity Discount problem
and describe how functional programs can easily be embedded within existing
imperative programming solution approaches.
2 - The Relational Algebra of Constraint Sets in Robust Optimization
G. N. Srinivasa Prasanna, International Institute of Information
Technology - Bangalore, 26/C Electronics City, Bangalore, India,
gnsprasanna@iiitb.ac.in
4 - Self Adaptation GA Applied to Routing Problems
Jaime Mora Vargas, Tecnológico de Monterrey, Research and
Graduate Division, Campus Estado de México, Mexico,
jmora@itesm.mx], Nestor Velasco-Bermeo, Miguel GonzàlezMendoza
A relational-algebra for identifying, classifying, & visualizing relationships among
different constraint sets (input assumptions) in a robust optimization (RO)
framework is presented. Set-theoretic relations between alternative constraint sets
are specified in an expression-based query language (composed of set-disjointness,
union, intersection, etc.) We can compare, visualize & analyze different sets of
assumptions, facilitating decision-support in general, & RO in particular.
Mathematical Programming (MP) has proven to be an effective strategy to tackle
down optimization problems. Traditional methods fail to solve such problems due to
the “combinatory explosion”, an exponential increase of the solution space
theorically identified as “NP-Hard” problems, based on such tendency new strategies
have been proposed; the combination of mathematical programming and hybrid
metaheuristics, the later having as main characteristic the adaptation ability to the
environment’s changes without the need to fine tune the parameters or re-run the
method. GA’s have proven to be one of the most successful methods to solve most
of the classic optimization problems. Though the benefits of such algorithms
disappear when situation analyzed changes. Based on such inconvenient a new
approach is proposed. A hybrid GA with MP and the incorporation of “autoadaptation” lets the algorithm not just to evolve solution candidates but its own
parameters based on the current state (individual’s aptitude according to each
generation). The problems solved are ; Vehicle Routing Problem With Time Window
(VRPTW) and Multi-depot Vehicle Routing Problem With Time Window
(MDVRPTW).
3 - Loading of Ships at Refineries when Arrival Times are Uncertain A Robust Optimization Approach
Jens Bengtsson, Norwegian School of Economics and Business
Administration, Helleveien 30, Bergen, Norway,
jens.bengtsson@nhh.no, Patrik Flisberg, Mikael Rönnqvist
Ships that arrive to refinery ports are either served from product or component
tanks. Arrival times of ships are uncertain and as such the inventory levels in the
tanks will be uncertain and can in extreme cases be full or empty. Both these
outcomes may be costly to the refiner. In this paper we take the arrival time
uncertainty into account and analyze the production planning and loading problem
by using robust optimization.
4 - The Newsvendor Problem with Ambiguous Demand Distribution
Bacel Maddah, Assistant Professor, American University of Beirut,
P.O. Box 11-0236 Riad El Solh, Beirut, 1107-2020, Lebanon,
bm05@aub.edu.lb, Ebru Bish, F. Jordan Srour, Kyle Lin
5 - A Compromised Large-scale Neighborhood Search Heuristic for
Heterogeneous VRP
Fan Wang, Prof., Sun Yat-sen Business School, Sun Yat-sen
fanwang@gmail.com, Yi Tao
We study the newsvendor problem when the demand distribution is “ambiguous” in
terms of being within a given Kullback-Leibler distance from a nominal distribution.
Our approach is novel as no precise estimate of demand parameters (e.g., moments,
percentiles, and range) is required. We derive the optimal newsvendor ordering
policy in this setting.
We addressed the Heterogeneous VRP with fixed costs and routing costs in which a
limited fleet of different vehicles is available for sending goods to customers with
known demand along the network with the objective of minimizing the total cost.
We propose a compromised large-scale neighborhood search heuristic where the
neighborhood aims to relax the subset-disjoint restriction during the process of
multi-exchange neighborhood search.
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WD45
3 - Controlling Epidemics over Multi-level Co-evolving Networks
Achla Marathe, Asociate Professor, Virginia Tech, CRC XV VBI,
Blacksburg, 24061, United States of America, amarathe@vbi.vt.edu,
Stephen Eubank, Bryan Lewis, Jiangzhou Chen, Madhav Marathe
Optimization Algorithms
Human behavior, epidemics and social contact networks are closely intertwined and
co-evolve. Effective planning and response strategies must take these complicated
interactions into account. We will describe an interactionist approach for studying
these co-evolving social systems with the goal of supporting public health
epidemiology. Individual and collective behavioral adaptation is critical in these
systems and will be highlighted via illustrative case studies.
(Joint Cluster ICS)
Sponsored Session
Chair: Ilya Safro, Argonne National Laboratory, 9700 S. Cass Avenue,
Argonne, IL, 60439, United States of America, safro@mcs.anl.gov
1 - Beyond Fisher’s Linear Dicriminant Function
Shuichi Shinmura, Professor, Seikei University, 3-3-1 Kichijoujikitamachi, Musashino, 180-8633, Japan, shinmura@econ.seikei.ac.jp
4 - Optimal Link Removal for Epidemic Control Over Networks
94035, United States of America, evaenns@stanford.edu, Jeff
Mounzer, Margaret Brandeau
Fisher founded linear discriminant function (LDF). LDF assume two groups are the
same normal distribution, nevertheless few data satisfy this assumption. If data
satisfy this, error rate equals to the minimum error rate (MNM). Therefore, LDF
should be defined by MNM criterion. Revised IPLP-OLDF looks for the estimate of
MNM using mixture of LP and IP. Evaluation of 13,500 models shows the mean of
error rates of Revised IPLP-OLDF using LINGO are less than those of LDF & logistic
regression.
Control of infectious diseases which spread through close contact often focuses on
interrupting the network of contacts. We examine the problem of determining
which links should be removed from a contact network to maximize infections
averted, given a constraint on the maximum number of links that can be removed.
We formulate the problem as a non-convex quadratically constrained quadratic
program. We evaluate the performance of approximate and heuristic solutions.
2 - A Separation Heuristic for Gap Inequalities
Konstantinos Kaparis, Dr., University of Southampton,
Southampton, SO17 1BJ, United Kingdom, K.Kaparis@soton.ac.uk,
Laura Galli, Adam Letchford
■ WD45
Laurent and Poljak introduced a class of valid inequalities for the max-cut problem,
called gap inequalities, which include many other known inequalities as special
cases. Even though they have received limited attention they can make very good
cutting planes for the Max-Cut problem. We describe a separation heuristic for these
and we present computational results which illustrate the potentials of the proposed
scheme.
Health Care, Other
Contributed Session
Chair: S.Reza Sajjadi, Post- Doctoral Research Fellow, North Dakota State
University, NDSU Department2485, 120A CIE, P.O.Box 6050, Fargo, ND,
58108-6050, United States of America, reza.sajjadi@ndsu.edu
1 - Feature Level Selection in Disease Clusters
Saylisse Davila, Arizona State University, 151 E Broadway Rd #210,
Tempe, AZ, United States of America, saylisse@asu.edu,
George Runger, Eugene Tuv
3 - Polynomial Complexity Algorithm for Integer
Transportation Problem
Vladimir Tsurkov, Prof., Computing Center of Russian Academy of
Sciences, Vavilov Str., 40, Moscow, 119333, Russia, tsur@ccas.ru,
Alexander Tizik
Most public health surveillance methods focus on detecting the presence of disease
clusters. However, identifying the specific location of disease clusters can be equally
important. Nowadays, health data is often recorded in large databases. Finding the
specific location of these disease clusters among a large number of records and
variables can be an intricate task. We will present a methodology that can be used
to identify the ranges and/or levels of variables that define the clusters.
A net optimization large scale problem from telecommunication area is solved by
means of the known method of column generation. The intermediate problem has
transportation kind of restrictions. Algorithm of polynomial complexity is proposed.
Method is based on iterative solutions of two-dimensional knapsack problems.
4 - Multiscale Approach for the Network Compression-friendly Ordering
Ilya Safro, Argonne National Laboratory, 9700 S. Cass Avenue,
Argonne, IL, 60439, United States of America, safro@mcs.anl.gov
2 - Impact of Medicare Part D on Generic Drug Utilization in Long Term
Care Facilities
Changmi Jung, Carnegie Mellon University, 4800 Forbes Ave.,
Rm 242, Pittsburgh, PA, 15213, United States of America,
changmi@andrew.cmu.edu, Rema Padman, Shamena Anwar
We present a fast multiscale approach for the network minimum logarithmic
arrangement problem. This type of arrangement plays an important role in a
network compression. The algorithm is of linear complexity and exhibits good
scalability which makes it practical and attractive for using on large-scale instances.
Its effectiveness is demonstrated on a large set of real-life networks.
This study examines the impact of Medicare Part D program on generic drug
prescription rates in Long Term Care Facilities. We analyze prescription orders from
a regional online pharmacy to induce a general pattern using the Difference in
Difference method on four different therapeutic drug classes.
■ WD44
3 - A Comparison of Drug Price Increases in the
Pharmaceutical Industry
Kathleen Martino, Rutgers University, 1 Washington Park, Newark,
NJ, 07102, United States of America, martinok2@gmail.com,
Yao Zhao
Network Modeling in Healthcare
Sponsored Session
Motivated by the current events regarding prescription drug prices, this empirical
study examines if factors such as therapeutic class, manufacturer, and active
ingredient levels play a role in the established price of prescription drugs. We
examine both the wholesale price set by manufacturers and the markup set by
distributors for both brand and generic drugs. We also quantify the difference
between brand and generic drug prices as a drug moves downstream from
manufacturers to pharmacies.
Chair: Eva Enns, Stanford University, 117 Encina Commons, Stanford,
CA, 94035, United States of America, evaenns@stanford.edu
1 - Modeling HIV Spread in Africa using Sexual Contact Network Data
Benjamin Armbruster, Northwestern University, 2145 Sheridan Road
(Tech Bldg), Evanston, IL, 60208-3119, United States of America,
armbruster@northwestern.edu, Stephane Helleringer
4 - Optimization of the Dynamic Operational Decisions for Ambulance
Dispatch: A Reallocation Model
Sandra Milena Santa, Universidad de los Andes, Carrera 1 N° 18A 12, Bogotà, CU, Colombia, sm.santa30@uniandes.edu.co, Andres
Correa, Ciro Alberto Amaya Guio, Nubia Milena Velasco Rodriguez
Using a unique data set from the Likoma Network Study, we examine the structure
of the sexual contact network, how it changes over time, and how this affects
models of disease spread.
2 - The Impact of the Health Delivery Supply Chain on Adherence to
HIV Treatment
Jessica McCoy, Stanford University, Stanford, California 94305,
United States of America,jhmccoy@stanford.edu, Eric Johnson
Ambulance dispatch as a response to some emergency medical services (EMS) needs
to be executed effectively meeting time response and coverage demand
requirements. Reallocation of ambulances gives the possibility of meeting and
improving these standards response, but it is important to have in mind that these
decisions carry transport costs and consume time. Therefore, we present a dynamic
model as a decision support tool that allows evaluating the necessity to update
location of ambulances.
Adherence to HIV treatment is a predictor of viral suppression, and transmission
rates are much lower in adherent populations. The health delivery supply chain in a
resource-limited region potentially creates or removes barriers for patients seeking
regular treatment. We develop a model to gain insights about the impact that the
supply chain has on patients’ ability to be adherent (and hence on HIV prevalence)
in a community.
447
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■ WD47
5 - Patient Flow in a Multiple-Route High-Variability Primary Care Clinic
S.Reza Sajjadi, Post- Doctoral Research Fellow, North Dakota State
University, NDSU Department2485, 120A CIE, P.O.Box 6050, Fargo,
ND, 58108-6050, United States of America, reza.sajjadi@ndsu.edu,
Jing Shi, Kambiz Farahmand
Project Management
Contributed Session
Simulation modeling of patient flow in an outpatient primary care clinic is
considered in this study. In schedule-based clinics where patient arrivals follow the
schedule given to the patients, inefficient layout and communication system as well
as variability increase the waiting time of the patients in the clinics and thus result
in patient dissatisfaction. Considering waiting time and distance traveled, the
simulation model investigates a number of scenarios to improve the current
situation.
Chair: Eduardo G. Hernandez-Martinez, PhD, Tecnologico de Estudios
Superiores de Coacalco, 16 de Septiembre 54, Coacalco, 55700, Mexico,
eghm2@yahoo.com.mx
1 - Analyzing Robustness of Team Communication-performance
Relationships
Deanna Kennedy, Assistant Professor, University of Washington,
Bothell, 1501 Copperfield Pkwy #412, College Station, TX, 77845,
United States of America, kennedy.deanna@gmail.com,
Rebecca Perryman, Sara McComb
■ WD46
Patterns in team communication relate to time and cost performance. We examine
optimality when tradeoffs are made between the two performance outcomes.
Further, we analyze the robustness of communication patterns by estimating the
performance of sampled data from hyperspheres centered at optimal points.
Implications are discussed.
Statistical Modeling and Analysis in Healthcare
Applications
Sponsored Session
2 - Ensuring OR/MS Project Success: A Change
Management Perspective
Robert Levasseur, Professor of Management, Walden University,
2614 Vista Cove Road, St. Augustine, FL, 32084-3069,
United States of America, robert.levasseur@waldenu.edu
Chair: Li Zeng, Assistant Professor, University of Texas at Arlington,
Industrial & Manuf. Sys. Engr. Department, Arlington, Tx, 76019-0017,
United States of America, lzeng@uta.edu
1 - Minimizing Rehospitalization Costs Through Machine Learning
Mohsen Bayati, Stanford University, 350 Serra Mall, Packard
Building, room 278, Stanford, CA, 94305, United States of America,
bayati@stanford.edu, Mark Braverman, Eric Horvitz
Research into the reasons for project failure suggests that a high percentage of those
failures are the result of non-technical problems, such as poor communication and
resistance to change. The purpose of this presentation is to explore ways in which
OR/MS project leaders can increase the odds of project success by applying basic
principles and practices of change management.
Nearly one in every five patients is rehospitalized within 30 days of their discharge.
In 2004 the estimated cost of unplanned readmissions to Medicare was $17.4
billion. In this talk, I will demonstrate how online machine learning and
optimization tools can be applied to electronic health records to identify patients
with the highest risk of rehospitalization. We validated these predictions on a major
hospital’s database and obtained cost-effective policies for minimizing
rehospitalizations.
3 - Theory of Latency in integrated Concurrent Engineering
States of America, john.m.chachere@nasa.gov, John Kunz,
Ray Levitt
We observed Stanford and NASA teams using Integrated Concurrent Engineering
(ICE) to accelerate conceptual design by a factor of ten. We assert that ICE teams
manage ten enabling factors that decimate information response latency, and thus
project duration. Latency is a unifying principle and a practical metric that can
describe, evaluate and manage engineering design collaboration. ICE is the “Just in
Time” of knowledge work; ICE flows information with minute latency and high
reliability.
2 - In-N-Out: An Energy Balance Model of Obesity
Joanna Lankester, PhD candidate, Stanford University, 300 Pasteur
Lane, Grant S131, Stanford, CA, 94305, United States of America,
jl3@stanford.edu, Margaret Brandeau, Julie Parsonnet
Obesity, which is associated with heart disease, diabetes, and other common and
sometimes life-threatening conditions, has increased in prevalence dramatically over
the last 50 years. To understand the rise in obesity, we are developing a model of
body weight in the U.S. population from a perspective of energy balance. The model
quantifies the changes over time in factors that influence body weight so that we
can explore variability in obesity between individuals with similar energy intake.
4 - New Method for Project Crashing using Excel Solver
Pamela Zelbst, Sam Houston State University, 1256 Avenue I,
Huntsville, TX, 77341, United States of America, mgt_pjz@shsu.edu,
Kunpeng Li, Bin Shao
3 - Reducing Medication Errors in Pediatrics
Michelle McGaha, PhD Graduate Student, Texas A&M University,
3131 TAMU, College Station, TX, 77843, United States of America,
michelle.mcgaha@neo.tamu.edu, Kiavash Kianfar, Lewis Ntaimo,
Amarnath Banerjee
We developed a new method for project crashing using Excel Solver. The method
uses AON network. The Excel formulation is much simpler and straightforward
than the traditional method using AOA network.
5 - A Discrete-event Approach for the Task Planning of
PMBOK-based Projects
Eduardo G. Hernandez-Martinez, PhD, Tecnologico de Estudios
Superiores de Coacalco, 16 de Septiembre 54, Coacalco, 55700,
Mexico, eghm2@yahoo.com.mx, Guillermo Torres
Medication errors are common in the complex setting of pediatric medicine. We
discuss the obstacles in determining the prevalence of pediatric medication errors
and present a taxonomy chart of the most common pediatric medication errors, as
well as defining characteristics for each error type. We discuss the challenges and
highlight prevention strategies and meaningful use of health IT in reducing
medication errors in the future.
This work presents an approach based on Supervisory Control Theory for the task
planning of projects based on the PMBOK. The goal is a formal strategy to obtain
automatically a gant chart considering all possible tasks concurrences according to
times, resources availability and resources sharing. Unlike the graph methods
reported on the PMBOK based on the user experience, the approach permits the
time optimization establishing only the resources list and the restrictions of the tasks
execution.
448
WD54
■ WD50
■ WD53
Information Systems III
Operations/Finance Interface
Contributed Session
Contributed Session
Chair: Yun Huang, Northwestern University, 4146 Oakton st #2, Skokie,
IL, 60076, United States of America, yun@northwestern.edu
1 - The Value of Information: Evidence of Decreasing Price Dispersion
in India’s Crop Market
Chris Parker, PhD Candidate, London Business School,
Regent’s Park, London, NW14SA, United Kingdom,
cparker.PhD2007@london.edu, Nicos Savva, Kamalini Ramdas
Chair: Amit Mitra, Auburn University, College of Business, Office of the
Dean & Department of Manag, Auburn, AL, 36849-5240,
United States of America, mitraam@auburn.edu
1 - Vicarious Learning From Operational Failures
Manpreet Hora, Georgia Institute of Technology, 800 W Peachtree St.
NW, Atlanta, GA, 30308, United States of America,
manpreet.hora@mgt.gatech.edu, Robert D. Klassen
This paper aims to measure the effect of a new text message based information
service on price dispersion empirically. Our dataset contains information about
several crops, with diverse supply chain characteristics, and information about the
adoption level of the technology. Having information about multiple crops allows us
to identify factors impacting different types of crops. Results show that adoption
levels are associated with lower price dispersion between markets.
The occurrence of a rare operational failure in a firm (incident firm) provides an
opportunity for vicarious learning for other firms (knowledge-seekers). Employing a
field experiment, we examine the firm-level characteristics that enable vicarious
learning. Results suggest that saliency of the incident firm and complementarities
between the incident firm and the knowledge-seekers have a positive association
with vicarious learning.
2 - Value From New Electronic Markets: A Diffusion Analysis of Two
Equity Options Exchanges
Chris Parker, PhD Candidate, London Business School,
Regent’s Park, London, NW14SA, United Kingdom,
cparker.PhD2007@london.edu, Bruce Weber
2 - Investigating the Impact of Operational Variables on Manufacturing
Cost by Simulation Optimization
Wen-Chyuan Chiang, Prof., Collins College of Business, The
University of Tulsa, The University of Tulsa, Tulsa, OK 74104, Tulsa,
United States of America, wen-chyuan-chiang@utulsa.edu,
Rui Zhang
Two all-electronic options exchanges opened for trading in 2000 and 2004. The
exchanges gained trading volumes in competition with four incumbent markets. To
explain the markets’ diffusion patterns, we model broker order routing decisions.
The model generates hypotheses, which we test using a panel of quarterly
disclosures from major brokerage firms. We conclude that firm heterogeneity is
more influential than network effects in explaining the diffusions of the new
markets at the broker level.
We focus on the relationship between operational variables (setup time, scrap rate,
downtime rate) and the manufacturing cost. Keeping such parameters low is
beneficial for reducing the average variable cost, but the required maintenance will
incur an additional fixed cost. Therefore, a simulation based optimization approach
is applied to determine the optimal level of the operational variables for minimizing
the average cost. Sensitivity analysis and explanations are also provided.
3 - An Online Retailer’s Incentive to Become an Online Marketplace
Kihoon Kim, Assistant Professor, Korea University Business School,
Anam-Dong, Seongbuk-Gu, Seoul, 136701, Korea, Republic of,
kihoonk@gmail.com
3 - Managing Operations Risks: An Options Perspective
Wei Chen, Katz Graduate School of Business, University of
Pittsburgh, 233 Mervis Hall, Pittsburgh, PA, 15260,
United States of America, wchen@katz.pitt.edu, Jennifer Shang
When an online retailer develops into an online marketplace, the online retailer can
invite other online retailers to sell the same product it deals with in the online
marketplace. This paper investigates under what conditions the online retailer is
advised to transform itself to the online marketplace, considering the online
retailer’s trade-off of its referral revenue against the loss of some of its loyal
customers. We also characterize optimal pricing structures of the online
marketplace.
When dealing with demand and supply uncertainties, operations managers must
also consider risks such as exchange rate variation, distribution cost surge, and
political upheaval. These uncertainties can significantly influence a firm’s
profitability. We address these risks from the perspectives of financial markets,
operations control, and stochastic programming, and show that real options is a
useful framework for understanding risk hedging in operations.
4 - An Integrated Model Utilizing R&D Costs for Two-dimensional
Warranty Policies
Jay Patankar, Professor, The University of Akron, Department of
Management, College of Bus. Administration, Akron, OH, 443254801, United States of America, jgp@uakron.edu, Amit Mitra
4 - IOS Appropriation and Net Enablement
Mei Cao, University of Wisconsin-Superior, Department of Business
and Economics, Superior, United States of America,
mcao1@uwsuper.edu, Qingyu Zhang
The objective of the study is to uncover the nature of IOS appropriation and net
enablement as an antecedent of supply chain collaboration. Reliable and valid
instruments were developed through rigorous empirical analysis including
structured interviews, Q-sort, and a large-scale study. Data were collected through a
Web survey of U.S. manufacturing firms in various industries. Predictive validity is
evaluated by demonstrating its strong relationship with supply chain collaboration.
Some consumer durables, such as automobiles, involve warranties involving two
attributes. These are time elapsed since sale of the product and usage of the product
at a given point in time. An avenue to impact warrant costs is through research on
product development. The objective then becomes to determine warranty
parameters, while constraining the sum of the expected unit warranty costs and
research and development costs per unit sales, under a limited research and
development budget.
5 - Encounter in Virtual Space
Yun Huang, Northwestern University, 4146 Oakton st #2, Skokie, IL,
60076, United States of America, yun@northwestern.edu,
Roger Chen, Noshir Contractor, Hani Mahmass
■ WD54
Many virtual worlds such as massively multiplayer online role-playing games
(MMORPGs) are often designed to mimic the real world along several dimensions,
including the spatial requirements for engaging in activities. This paper examines
the impact of virtual “geographical distance” between players in EverQuest II on the
process of relation building in game. The results show that players are more likely to
meet and interact with each other if they have more overlapping activity spaces.
Technology Management
Sponsored Session
Chair: Gulru Ozkan, Assistant Professor, Clemson University, Department
of Management, 101 Sirrine Hall, Clemson, SC, 29634, United States of
America, gulruo@clemson.edu
1 - Better Selection or Efficient Contracting?: A Model of Knowledge
Vendor Selection and Contracting
Zhijian Cui, PhD Candidate, INSEAD, Constance de Blvd,
Fontainebleau, France, Zhijian.CUI@insead.edu, Sameer Hasija
We are studying the vendor selection and contracting issue for knowledge driven
processes. In particular, we study three vendor selection process: (1)Selection is
based on initial talks with the vendor and subsequently the contract is negotiated
with the selected vendor. (2)The vendors are informed about the SLA and asked to
bid for the contract. (3) The vendors are asked to propose a contract to the client.
449
WD55
2 - Innovation in Top-Down and Bottom-Up Strategy Processes
Fabian Sting, INSEAD, Boulevard de Constance, Fontainebleau,
France, fabian.sting@insead.edu, Christoph Loch
4 - Realizing the Value of RFID in a Global Enterprise
Ann Marucheck, Professor, Kenan-Flagler Business School, McColl
Bldg CB 3490, UNC-Chapel Hill, Chapel Hill, NC, 27599, United
States of America, ann_marucheck@unc.edu, Noel Greis,
Monica Nogueira, Anders Duus, Hong Tham Nguyen
We study strategy processes at six German manufacturing organizations using an
organizational search perspective. While the final decision on strategic initiatives
remains at the top, strategic initiatives are distributed across hierarchical levels,
depending on where expertise is concentrated. The organizations also use multiple
mechanisms to coordinate decentralized actors. Coordination and top-down decision
making is weighed against the creativity that stems from delegated search.
For many organizations, understanding the potential benefits of RFID and justifying
its investment continue to be challenges. In this research, we comprehensively
study over 4000 cases of RFID projects as reported in the IDTechEX database.
Specifically, we contrast the benefits realized by early adopters of RFID with more
recent adopters. We further suggest measures that can determine how RFID
provides economic value to an enterprise and identify the drivers of determining
that value.
3 - Managing New Product Development Knowledge for Competing
Firms: Case of Joint Development
Gulru Ozkan, Assistant Professor, Clemson University,
Department of Management, 101 Sirrine Hall, Clemson, SC, 29634,
United States of America, gulruo@clemson.edu, Cheryl Gaimon
■ WD56
We introduce a stochastic game on knowledge sharing (KS) and knowledge
development (KD) strategies for two NPD firms. First, leader sets allocations of
profit, then firms decide on KS for joint development of a new product. Next, firms
jointly pursue KD and launch the product. Insights include impact of uncertainty.
C - Room 1, Level 1
Simulation and Optimization II
Contributed Session
4 - A Decision Model to Manage Network Security Technologies for
Information Assurance
Soumyo Moitra, Senior Member of Technical Staff, Software
Engineering Institute, Carnegie Mellon University,
4500 Forbes Ave, Pittsburgh, PA, 15213, United States of America,
smoitra@sei.cmu.edu
Chair: Xueping Li, Assistant Professor, University of Tennessee,
408 East Stadium Hall, Knoxville, TN, 37996, United States of America,
Xueping.Li@utk.edu
1 - Allocating Manpower to Minimize Lmax in a Job Shop
Benjamin Lobo, North Carolina State University, 400 Daniels Hall,
College of Engineering, Raleigh, NC, 27695, United States of
America, bjlobo@gmail.com, James Wilson, Thom Hodgson,
Russell King, Kristin Thoney
This paper describes a model to manage technologies to protect informational assets.
The focus is on the valuation of information and a methodology to arrive at the
value at risk is presented. This assessment is used by the model to evaluate the
benefits of different levels of security technologies. Sensitivity analysis with respect
to the value of information is presented.
Most job shops are constrained not only by machines, but also by the number of
workers available to operate these machines. Different worker allocations to
machine groups can impact the Lmax value of a schedule. Using a relaxation of the
problem to generate a lower bound on Lmax, we develop a procedure to allocate
workers to machines that minimizes this lower bound. Computational experience is
presented.
■ WD55
2 - Improved Fully Sequential Procedure with Mean and
Variance Update
Huizhu Wang, Georgia Institute of Technology, 765 Ferst Dr, Atlanta,
GA, 30332-0205, United States of America, huizhuwang@gmail.com,
Seong-Hee Kim
Inventions, Innovation and Technology Management
Sponsored Session
Chair: Kun Liu, Assistant Professor, Wayne State University,
5201 Cass Ave, Detroit, United States of America, ek9525@wayne.edu
1 - Abandonment of Patented Inventions in
Innovation-Intensive Industries
Kun Liu, Assistant Professor, Wayne State University, 5201 Cass Ave,
Detroit, United States of America, ek9525@wayne.edu
Ranking and selection (R&S) procedures compare a number of simulated systems
and try to find a system with the best performance measure. Fully-sequential R&S
procedures are shown to be efficient but its probability of correct selection tends to
be higher than the nominal level especially for a large number of systems. We study
sources for conservativeness and present a procedure with improved efficiency.
3 - Simulation-based Optimization and Stochastic Programming
Tahir Ekin, PhD Candidate, George Washington University,
2201 G Street, NW Funger 415, Washington, DC, 20052, United
States of America, ekin@gwu.edu, Refik Soyer, Nicholas Polson
Little research has examined how firms abandoned some inventions in innovationintensive industries. Distant innovation search is associated with a greater
technological distance between newly acquired inventions and abandoned
inventions, as well as a younger average age of abandoned inventions. Abandoning
younger inventions and more focused abandonment of inventions are associated
with greater market value as measured by Tobin’s Q.
We provide a simulation-based approach to optimization and stochastic
programming. First, we consider a Monte Carlo solution to linear programming and
then show that it naturally extends to two-stage stochastic programming with
uncertainty. One advantage of our approach is that it is straightforward to add
parameter uncertainty and does not need derivative information.
2 - Continuous Quality/Time/Cost Tradeoffs
Bruce Pollack-Johnson, Associate Professor of Mathematical
Sciences, Villanova University, 800 Lancaster Avenue, Villanova, PA,
19085, United States of America, bruce.pollackjohnson@villanova.edu, Matthew Liberatore
4 - Parametric Moment Closure of Non-linear State Dependent
Stochastic Systems
Ritesh Arora, Graduate Research Assistant, Missouri University of
Science and Technology, Dpt. of Engg. Management & Systems
Engg., Rolla, MO, 65409, United States of America,
ra95d@mail.mst.edu, Ivan Guardiola
We use an example of a translation project to illustrate how quality can be modeled
as a continuous function of time and cost. Given a project deadline and budget,
overall quality can then be maximized using a nonlinear programming model.
Alternatively, iso-quality curves can be drawn, to visualize the continuous tradeoffs
between time, cost, and quality, and then used to pick a combination that seems
best for a particular situation.
This research highlights the use of parametric moment closure approximations for
non-linear stochastic systems. A general birth-and-death non-linear stochastic
process will be analyzed and closed under various underlying parametric
distribution assumptions. It results that closure under neglect is considerably less
robust than parametric closure. We highlight this theoretical endeavor through an
analysis of aphid population stochastic model.
3 - Launching Technologically Advanced Products in
Segmented Markets
John N Angelis, Rochester Institute of Technology,
105 Lomb Memorial Drive, Rochester, United States of America,
jangelis@saunders.rit.edu
5 - Simulation and Optimization of Supply Chain Models
for Supercomputing
Xueping Li, Assistant Professor, University of Tennessee, 408 East
Xueping.Li@utk.edu, Zhe Zhang
We focus on how competing profit-maximizing firms should set price and quality
for a new technologically-advanced product sold to a segmented market. We
analyze a closed-loop Stackelberg game with perfect information. If the late entrant
possesses a large enough cost disadvantage, it should only target the least innovative
segment. We also find that a firm with a large cost advantage may not necessarily
earn higher profits by being the first mover.
Cache design is a great challenge in data management in supercomputing and a key
component to improve the performance by storing data for future access. It is in the
similitude of behaviors of a supply chain in which suppliers attempt to meet the
demands from customers. We develop, simulate and optimize supply chain models
for the cache design of supercomputers and evaluate the performances.
450
WD61
■ WD57
■ WD58
C - Room 2, Level 1
C - Room 3, Level 1
Portfolio Analysis
Financial Engineering II
Contributed Session
Contributed Session
Chair: Mark Zschocke, University of Waterloo, 200 University Avenue
West, Waterloo, ON, N2L3G1, Canada, mszschoc@uwaterloo.ca
1 - The Efficient Frontier for Weakly Correlated Assets
Xili Zhang, Research Associate, School of Business
Administration,South China University of Technology,
381 Wushan Road, TianHe District, Guangzhou, 510641, China,
zhangxili831@gmail.com, Michael J. Best
Chair: Stephen Stoyan, University of Southern California, 3715
McClintock Avenue, GER 240, Los Angeles, CA, 90089, United States of
America, stoyan@usc.edu
1 - Corporate Cash Holding, Production and Investments Applied to
the Agribusiness Sector
Astrid Prajogo, Princeton University, ORFE Deparment,
Sherrerd Hall, Princeton, NJ, 08544, United States of America,
aprajogo@princeton.edu, John Mulvey, Davi Valladao
Best and Hlouskava have shown that for a Markowitz portfolio selection problem
having a diagonal covariance matrix and no short sales constraints, the efficient
frontier is traced out in a monotonic fashion whereby assets are reduced to zero and
subsequently remain at zero in order of their expected returns. We show that if the
correlation matrix of the assets is “nearly” diagonal (in a sense to be made precise)
then the efficient frontier will be traced out in a similar way.
We propose a multistage stochastic program of a firm facing uncertain investment
opportunities and a convex cost of external financing. The model endogenously
determines the best production, investment, financing and cash holding policies
over the planning horizon. The implications of corporate cash holdings are
illustrated for the agricultural sector.
2 - Sharpe Ratios and Implied Risk Free Rates
Michael J. Best, Professor, University of Waterloo,
200 University Avenue West, Waterloo, ON, N2L 3G1, Canada,
mjbest@uwaterloo.ca
2 - Efficient Monte Carlo Barrier Option Pricing Under a
Jump-Diffusion Process
Samim Ghamami, University of Southern California,
University Park Campus, Los Angeles, CA, United States of America,
ghamami@usc.edu, Sheldon Ross
For the usual mean-variance Markowitz portfolio optimization model having just a
budget constraint, the choice of a market portfolio implies a unique risk free rate.
However, practical portfolio optimization problems have many inequality
constraints. These constraints may cause kinks or points of non-differentiability on
the resulting efficient frontier. We show that choosing a kink point as a market
portfolio results in a continuum of implied risk free rates and give a formula for
them.
We present efficient simulation procedures for pricing barrier options when the
underlying security price follows a geometric Brownian motion with jumps.
Metwally and Atiya [2002] developed a simulation approach in the same setting for
pricing knock-out options, but no variance reduction was introduced. We improve
upon M&A’s approach by innovative applications of well-known variance reduction
techniques. We also show how to use simulation to price knock-in options.
3 - Goal Programming Models for Mutual Funds Portfolio Selection
From Global Markets
Mehrdad Tamiz, Professor, Kuwait University, College of Business
Administration, Kuwait City, Kuwait, mtamiz@yahoo.co.uk
3 - Optimal Execution Strategy in the Presence of Price Impact
Mauricio Junca, University of California, 4141 Etcheverry Hall,
Berkeley, CA, United States of America, mjunca@berkeley.edu
An investor needs to execute a long position in the asset by selling at discrete points
in time, affecting the price of the asset and possibly incurring in a fixed transaction
cost. The objective is to maximize the discounted revenue. This problem is
formulated as an impulse control problem and we characterize the value function
using the viscosity solutions framework. We also analyze the case where there is no
transaction cost and how this formulation relates with a singular control problems.
A vast number of criteria can be taken into consideration in portfolio selection other
than expected return and variance of return. This talk examines several factors
representing criteria in a Goal Programming setting for Portfolio Selection of mutual
funds. The selection is from 20 mutual funds from 10 countries representing 7
regions, with 7 factors that belong to mutual funds attributes, macroeconomics and
regional preferences.
4 - An Algorithm for Portfolio Problems with Discrete
Choice Constraints
Stephen Stoyan, University of Southern California,
3715 McClintock Avenue, GER 240, Los Angeles, CA, 90089,
United States of America, stoyan@usc.edu
4 - Servitization, Alliance, and Firm Value
Yeonsung Yoo, Korea University Business School, Anam-dong,
Seongbuk-Gu, Seoul, 136-701, Korea, Republic of,
yooys@korea.ac.kr, Hosun Rhim
We examine impacts of strategic alliance to the shareholder value by measuring the
stock market reaction associated with companies’ alliance announcements. Firms
are categorized to understand the impacts of servitization and productization.
Sample includes Fortune 500 companies.
We consider portfolio models that incorporate a comprehensive set of realistic
financial constraints, one of which includes the number of securities to hold.
Uncertainty is considered in the design through the use of stochastic programming.
The resulting large-scale problem forms a mixed-integer program, where we present
a model specific decomposition algorithm that generates solutions in reasonable
time. Computational limitations involved with the approach will also be discussed.
5 - Competitive Project Portfolio Management
Mark Zschocke, University of Waterloo, 200 University Avenue
West, Waterloo, ON, N2L3G1, Canada, mszschoc@uwaterloo.ca,
Benny Mantin, Beth Jewkes
■ WD61
We develop a Competitive Project Portfolio Management (CPPM) model wherein
two competing firms consider investing into two projects targeting, separately, a
mature and an emerging market. The returns firms obtain from investments into
these markets follow an s-shaped curve and depend on both firms’ actions. We find
that different forms of interactions may arise and outline optimal CPPM strategies.
We also discuss the market conditions that can lead to these outcomes.
Supply Chain, Risk Management
Contributed Session
Chair: Cigdem Gurgur, Professor, Purdue University, Doermer School of
Business, 2101 East Coliseum Blvd., Fort Wayne, IN, 46805,
United States of America, gurgurc@ipfw.edu
1 - Incentives to Invest in Multi-layer IT security Defense in
Supply Chain Firms
Tridib Bandyopadhyay, Assistant professor, Kennesaw State
University, 1000 Chastain Road, Kennesaw, GA, 30144,
United States of America, tbandyop@kennesaw.edu, Dengpan Liu,
Srinivasan Raghunathan
Supply chain firms have integrated business processes. This makes their IT risk
interdependent. Multilayer IT security defense works like stage-gates, bringing
interdependency between the efficacies of the successive layers. Thus SC firms face a
complex inter-firm, inter-layer IT security investment decision scenario. We provide
a game theoretic model that captures above multi-faceted interdependencies of IT
security risk in SC firms, and analyze their incentives to invest in IT security.
451
WD63
2 - Supplier Selection in Make-to-order Environment with Risks
Tadeusz Sawik, Professor, AGH University of Science & Technology,
Department of OR & IT, Krakow, 30059, Poland,
ghsawik@cyf-kr.edu.pl
3 - Census Uncertainty and Congressional Reapportionment
Dennis Leber, National Institute of Standards and Technology,
100 Bureau Dr, Gaithersburg, MD, 20899-8980, United States of
America, dennis.leber@nist.gov, Jeffrey Herrmann
A mixed integer programming approach that uses conditional value-at-risk via
scenario analysis is proposed for supplier selection and order allocation in supply
chains with risks. Given a set of customer orders for products, the decision maker
needs to decide from which supplier and when to purchase parts required for each
order to meet its due date and to mitigate the impact of low probability supply
disruptions and high probability supply delays.
The U.S. Constitution requires a decennial census, the results of which are used for
the reapportionment of congressional representatives. The census results are only
estimates and contain uncertainty. The Census Bureau can quantify this uncertainty
through statistical sampling, but this uncertainty is ignored during reapportionment.
This talk will present decision methods that consider attribute value uncertainty and
apply these methods to the problem of reapportioning congressional seats.
3 - A Multi-Product Risk-Averse Newsvendor with Exponential
Utility Function
Sungyong Choi, Rutgers University, 1 Washington Street,
Room #1072, Newark, NJ, 07102, United States of America,
sungyongchoi@gmail.com, Andrzej Ruszczynski
4 - A Decision Analysis Approach to Enterprise Risk Management
Jing Ai, A Decision Analysis Approach to Enterprise Risk
Management, The University of Hawaii at Manoa, Shidler College of
Business, 2404 Maile Way C305, Honolulu, HI, 96822,
United States of America, jing.ai@hawaii.edu, Tianyang Wang
We consider a risk-averse multi-product newsvendor using an exponential utility
function. We study the asymptotic behavior of the solution with respect to the
number of products and degree of risk aversion. Then, under reasonable conditions,
we obtain closed-form approximation which are easy to compute and much more
accurate than the risk-neutral solution. Then we obtain the analytical and
numerical insights for the interplay between risk aversion and demand dependence
structure.
Enterprise Risk Management (ERM) is an emerging corporate risk management
concept that proposes to manage risks in an integrated strategic system. One of the
most important challenges in ERM is the modeling of corporate decision making
process in light of dependent risks associated with fragmented business activities.
This paper presents a decision analysis approach to accomplish this task. It serves as
a practical guideline for managers to optimally allocate resources given risk
considerations.
4 - Flexible Supply Contract Design using Options in Apparel
Supply Chain
Bong-Sung Chu, Keio University, 3-14-1, Hiyoshi, Kohokuku,
Yokohama, Japan, superkensin@yahoo.co.jp, De-Bi Cao
■ WD64
The major risks in a supply chain mostly come from mismatch of supply and
demand with the dynamic demand changes. To avoid the risks, nowadays, flexible
supply contract models using options are attracting significant attention. This paper
addresses the flexible supply contract design with various types of financial options
which give holders the right and opportunity to be guaranteed a certain trading
quantity without stock out or opportunity loss in a single-period two-stage supply
chain.
Health Care, Strategy and Policy
Contributed Session
Chair: Vikram Tiwari, Assistant Professor, University of Houston,
2200 Business Center Dr, Apt 5104, Pearland, TX, 77584,
United States of America, vtiwari@Central.UH.EDU
1 - Clostridium Difficile: System Dynamics Modelling of Hospital
Infection Outbreaks
David Lane, Reader in Management Science, London School of
Economics, Houghton St., London, WC2A 2AE, United Kingdom,
d.c.lane@lse.ac.uk, Diogo Quintas, Alec Morton
5 - Competition, Diversification and Supplier Selection Under
Supply Disruptions
Cigdem Gurgur, Professor, Purdue University, Doermer School of
Business, 2101 East Coliseum Blvd., Fort Wayne, IN, 46805,
United States of America, gurgurc@ipfw.edu
In this study we consider supplier selection and quantity allocation decisions for a
single firm facing supply unreliability and demand uncertainty. We use a traditional
newsvendor framework to determine the optimal number of suppliers to place an
order with and the corresponding quantities of those orders. We explicitly address
the strategic behavior of suppliers in pricing decisions and we show how the pricing
decisions of the suppliers change in response to procurement decisions.
LSE and UK National Audit Office staff constructed a simulation model to
understand and control Clostridium difficile outbreaks. Different contamination
stages, various transmission mechanisms and bed, toilet and staff hand cleaning
were represented. The model synthesised information from a range of sources. It
also allowed users to explore and understand the complex consequences of the
interaction of a number of transmission vectors and policy interventions aimed at
combating outbreaks.
■ WD63
2 - Outcome Quality and Efficiency - A Healthcare Perspective
Scott Lindsey, University of Utah, Operations and Information
Systems, Salt Lake City, UT, United States of America,
scott.lindsey@business.utah.edu, Sriram Thirumalai
Decision Analysis VI
This study explores relationships between and operational drivers of outcome
quality and efficiency within healthcare operations. In the hospital setting, these
drivers include process standardization, operational focus, and operational
effectiveness. The study involves the use of stochastic frontier analysis based on data
from the U.S. Department of Health and Human Services and State of California.
Study findings, limitations and directions for future research are identified.
Contributed Session
Chair: Jing Ai, A Decision Analysis Approach to Enterprise Risk
Management, The University of Hawaii at Manoa, Shidler College of
Business, 2404 Maile Way C305, Honolulu, HI, 96822,
United States of America, jing.ai@hawaii.edu
1 - Novel Methods to Support Decision Making and Communicating
about Risks in Distributed Environments
Bonnie Ray, Manager, Risk Analytics, IBM T. J. Watson Research
Center, P.O. Box 218, Yorktown Heights, NY, 10598, United States of
America, bonnier@us.ibm.com, Lea Deleris
3 - Comparison of Markov and Discrete Event Simulation Models for
Advanced Prostate Cancer
Lanting Lu, Associate Research Fellow, Peninsula College of
Medicine & Dentistry, Veysey Building, Salmon Pool Lane, Exeter,
EX2 4SG, United Kingdom, lanting.lu@pms.ac.uk
This work compares discrete event simulation (DES) cost-utility model and Markov
cost-utility model built for an economic evaluation of a health technology degarelix,
for advanced prostate cancer, and highlights the differences in the assumptions, the
input data requirements and outcome estimations. The DES model gives more
accurate and detailed outputs and conducting a probabilistic sensitivity analysis
using the simulation model is found to be more straightforward than using the
Markov model.
I provide an overview of a current joint research initiative between IBM Research,
IBM Dublin, and University College Cork, partially funded by IDA Ireland. The
research focuses on development of new methods to 1)extract risk information from
text to form probabilistic graphical models using NLP techniques, 2)reason about
risk when probabilistic information is imprecise, 3)plan for risk in complex
environments using stochastic CP techniques and 4)communicate about risks in
distributed settings.
2 - A Comparison of Simultaneous Kelly Betting Strategies
Andrew Grant, University of Sydney, H69 Economics and Business
Bldg, Cnr Codrington and Rose Sts, Darlington, NS, 2008, Australia,
andrew.grant@sydney.edu.au, Peter Buchen
We consider the problem of Kelly betting on simultaneous games, and the relative
performance of betting strategies that use multi-bets compared to those that do not.
We develop a simulation model to test the performance of three Kelly betting
strategies using the empirical odds distribution from the 2007-08 English Premier
League Season. The results suggest that using multi-bets of all levels outperforms
the portfolio optimization approach of betting on single game outcomes only.
452
4 - Operating Room Utilization Study
Jihan Wang, Ph.D Student, Wayne State University, 4815 4th Street,
Rm. 2033, Detroit, MI, United States of America,
aw0984@wayne.edu, Kai Yang, Susan Yu
■ WD67
The successful management of operating rooms (OR) is very important
measurement to any hospital. The OR utilization is a well-acknowledged metric to
evaluate the performance of the facility. This research investigated 11 factors that
people think will impact the utilization, such as first case delays and case
cancellations. We determined the most important factors affecting utilization
through statistical analysis of the data from Detroit VA medical center.
Contributed Session
WD68
Transportation, Freight II
Chair: Dung-Ying Lin, Assistant Professor, National Cheng Kung
University, No. 1 University Road, Department of Transportation and
Commun., Tainan City, Taiwan - ROC, dylin@mail.ncku.edu.tw
1 - An Integrated Analysis on Global-US Freight Network
Jiahui (Carol) Wang, Research Assistant, University of Oklahoma,
202 W. Boyd St., Room 124, Norman, OK, 73019, United States of
America, jiahuiwang@ou.edu, Guoqiang Shen, P. Simin Pulat
5 - Incentive Games in Healthcare Delivery: Pay-for-Performance in
Primary Care
Vikram Tiwari, Assistant Professor, University of Houston,
2200 Business Center Dr, Apt 5104, Pearland, TX, 77584,
United States of America, vtiwari@Central.UH.EDU, Ana Groznik
This research studies on US international freight transportation by an integrated
view on global freight network and domestic freight network, in which, the
international freight flows are extended between US ports to final
destinations/origins (state, census tract, traffic analysis zone…, and the final census
block level). This research also provides insights into the impact of international
freight flows on domestic freight flows starting from each port.
In existing compensation system, primary care physicians’ reimbursement from
health insurance companies is not tied to patients’ long-term health outcome. Using
stylized two-stage game theoretical models we compare some structural options of
payments for physicians in the pay-for-performance market. We identify the
tradeoffs faced by physicians and insurance companies and derive necessary
conditions for different reimbursement structures to be optimal (tied to different
patient characteristics).
2 - Discrete Time Formulation for the Assignment Problem Applied in
Cross Docking Facilities
Georgios Saharidis, Professor, University of Thessaly and Kathikas
Institute of Research and Technology, Pedion Areos, Volos, 38334,
Greece, saharidis@gmail.com, Mihalis Golias
■ WD65
A cross-docking facility is a freight distribution facility representing a critical point in
a supply chain. The scheduling of the inbound trucks at a cross docking facility is a
classical assignment problem. In this paper two mathematical formulations are
presented to schedule inbound trucks to doors at a cross-docking facility, and
compared to the classical machine scheduling formulation.
Supply Chain, Shipping and Transportation
Contributed Session
3 - Scheduling Commercial Vehicle Queues at a Canada-US
Border Crossing
Michael Haughton, School of Business & Economics, Wilfrid Laurier
University, Waterloo, ON, Canada, mhaughton@wlu.ca,
K.P. Sapna Isotupa
Chair: Fatih Mutlu, Assistant Professor, Qatar University, Industrial
Engineering Department, Doha, 2713, Qatar, fatihmutlu@qu.edu.qa
1 - Cost Benefit Analysis of the Cargo Screening Processes using
Alternative Evaluation Methods
David Menachof, Peter Thompson Chair in Port Logistics, University
of Hull Logistics Institute, Cottingham Road, Hull, HU6 7RX, United
Kingdom, D.Menachof@hull.ac.uk, Uwe Aickelin, Galina Sherman,
Peer-Olaf Siebers
Using the context of queue operations at a major Canada-U.S. commercial border
crossing for truck-borne trade flows, we report on a computer simulation study to
predict the likely impacts of smoothing those flows. We quantify the operational
and resource efficiencies of flow smoothing, not only for trans-border trucking
companies and other commercial organizations involved in trans-border supply
chains but also for government authorities with regulatory jurisdiction at border
crossings. Our study achieves two major goals. First, it extends the queueing
literature’s range of settings in which queue management systems based on flow
smoothing are studied. Second, it adds quantitative precision to the post-9/11
discourse on reducing impediments to the performance of commercial trucking
operations that support trans-border supply chains.
Cost benefit analysis using three different methods, scenario analysis, decision trees
and simulation, are conducted. These methods are examined in a real world
situation and compared to actual data using different probabilistic methods of
estimating costs for port security risk assessment studies. Results show that in simple
situations, all methods can be equally used. As complexity increases, we show how
these tools can be used and focus on the limitations of each method.
2 - Distributor’s Integrated Inventory and Shipment Decisions
Sudarsan Rangan, Texas A & M University, 4217 TAMU, College
Station, TX, United States of America, srangan@mays.tamu,edu,
Ismail Capar, Malini Natarajarathinam
4 - Quantifying the Value of Information Sharing in Supply Chain
Inventory Management
Dung-Ying Lin, Assistant Professor, National Cheng Kung University,
No. 1 University Road, Department of Transportation and Commun.,
Tainan City, Taiwan - ROC, dylin@mail.ncku.edu.tw, Nai-Wen Hsu
This analysis is based on a problem faced by a spare parts distributor that supplies n
retailers. The distributor has to decide on his inventory system and replenish retailer
inventories using a VMI policy. We analyze this problem to provide optimal
inventory acquisition and shipment decisions to minimize the overall cost at the
distributor.
We first develop a model in which each stakeholder in the supply chain
independently chooses the optimal inventory policy that has the lowest total
expected cost (TEC) with stochastic demand. Then a model recognizing the
inventory coordination is developed to estimate the total expected cost of the
coordinated supply chain. The value of information sharing in supply chain
inventory management is quantified by the difference of TECs between these two
models.
3 - The Impact of Ship Unloading Time Variability on Port Selection
Cesar Meneses, Research Assistant, Arizona State University,
University Drive and Mill Avenue, Tempe, AZ, 85287, United States
of America, cesar.meneses@asu.edu, Rene Villalobos
We develop a port selection model based on additional inventory costs caused by
the variability of service times observed between the arrival of a ship to a port and
the time a container is released from the port. In particular, we seek to minimize
total landed costs by selecting the proper port.
■ WD68
4 - Contract Problems Between a Retailer and a For-Hire Carrier
Fatih Mutlu, Assistant Professor, Qatar University, Industrial
Engineering Department, Doha, 2713, Qatar, fatihmutlu@qu.edu.qa
Strategy/Strategic Planning II
We study transportation contract problems between a retailer and a for-hire carrier
delivering retailer’s replenishments. We model a decentralized carrier-retailer
channel and design frameworks to set contract terms according to individual
incentives. The terms are i) freight rate, which is based on a two-part tariff
structure, and ii) shipment size. We also analyze the centralized channel to
benchmark the channel profits. We propose modifications on the initial contracts to
assure coordination.
Chair: Michael Bean, Forio Business Simulations, 333 Bryant Street,
San Francisco, CA, 94133, United States of America, mbean@forio.com
1 - A Representation Model and Innovation Heuristics for Business
Ecosystems of Product-Service Systems
Minjeong Baek, Master Student, Seoul National University, 599
Kwanakro, Kwanakgu, Seoul, Korea, Republic of,
kelly706@snu.ac.kr, Changmuk Kang, Yoo S. Hong
Contributed Session
A business ecosystem is growing more complex in recent days, as more products
and services are integrated as a product-service system, and more stakeholders are
involved. This study presents a rigorous model for representing and analyzing a
business ecosystem consisting of various stakeholders that interact with products
and services. Based on this model, six heuristic rules for innovating an ecosystem
and industry cases have been proposed.
453
WD69
2 - The Demand-side Dynamics of Firms’ Intra-industry Exit in a
Geographically Fragmented Industry
Lalit Manral, Assistant Professor, University of Central Oklahoma,
100 N Universtiy Drive, Edmond, OK, 73034, United States of
America, lmanral@uco.edu, Kathryn Harrigan
4 - Creating Value Through Product Stewardship and Take-Back
Ronald Lembke, Associate Professor, Supply Chain, University of
Nevada, MGRS /0028, Reno, NV, 89557, United States of America,
rtl@unr.edu, Zac Rogers, Dale Rogers
Secondary markets provide a place for unwanted items to be bought and sold,
which diverts them from landfills, reducing the products’ ecological impact and
creating economic value. Secondary markets divert a large number of products from
landfills and create jobs, resulting in substantial economic value in the process.
Although not reflected in current government metrics, a conservative estimate is
that the secondary market represents 2.28 percent of the 2008 U.S. GDP.
This paper explores the demand-side dynamics of firms’ selective exit from
geographic sub-markets in a geographically fragmented industry. It provides
theoretical arguments and empirical evidence to explain how the demand-side
structural conditions differentially influence firms’ choice to manage their
geographic scope over time. A unique panel dataset drawn from a natural
experiment in the US long-distance telecommunications services industry during
1984-1996 is used to test the hypotheses.
■ WD70
3 - Strategic Capacity Investment and Pricing Decisions for
Substitutable Products with Partial Flexibility
Sharethram Hariharan, Graduate Research Associate, Oklahoma
State University, 322 Engineering North, OSU Stillwater, Stillwater,
ok, 74078, United States of America, sharethramh@gmail.com,
Tieming Liu, Ho-Yin Mak, Z. Max Shen
Optimization Models in Air Traffic Management
Sponsored Session
We study the capacity investment and responsive pricing decisions for a firm facing
random demands for two substitutable products. Resources are partially flexible. A
resource can be used to produce the other type of product, but with some efficiency
loss. We evaluate the impacts of demand variability, correlation and risk-aversion on
these decisions.
Chair: Andrew Churchill, Graduate Research Assistant,
University of Maryland, 1173 Martin Hall, College Park, MD, 20742,
United States of America, churchil@umd.edu
1 - The Impact of Induced Technological Change on Air Traffic
Management
Megan Ryerson, Institute of Transportation Studies, 109 McLaughlin
Hall, UC Berkeley, Berkeley, CA, 94720, United States of America,
msmirti@berkeley.edu
4 - Creating Web-based Simulations and Interactive Data Visualizations
Michael Bean, Forio Business Simulations, 333 Bryant Street, San
Francisco, CA, 94133, United States of America, mbean@forio.com
Simulations and interactive data visualizations that run in browsers have the
advantages of global accessibility, simple distribution, and the ability to monitor and
collect data on usage. However, simulations need to be modified in order to
effectively use the online medium. Usability design is critical to create simulations
that will be used by a diverse, global audience with limited knowledge of
simulation, short attention spans, and unarticulated use objectives.
Short-haul aviation is a focus of transportation policy today due to growing aircraft
diversity and uncertainty surrounding carbon emissions policies. We develop an
analytic total logistics cost model of short-haul corridor serving multiple passenger
groups and find that turboprops, alone and in a fleet mix with jets, minimize cost
for levels of policy seen today. This aircraft mix in response to a carbon emissions
policy has implications for air traffic management.
2 - Converging Upon Basic Feasible Solutions Through
Dantzig-Wolfe Decomposition
Joseph Rios, NASA, Mail Stop 210-15, Moffet Field, CA, 94035,
United States of America, Joseph.L.Rios@nasa.gov, Kevin Ross
■ WD69
Reverse Logistics II
We derive an important property for solving integer programs by examining the
master problem in Dantzig-Wolfe Decomposition. Namely, if a linear program can be
decomposed appropriately, a mapping exists between basic feasible solutions in the
master and original problems. This has implications for integer programs where the
convex hull has mostly integer corner points. We highlight the significance through
experiments on a large-scale traffic flow model for the National Airspace System.
Sponsored Session
1 - An Optimization Model to Determine Product Servicing Policies in
Green Supply Chains
Ruth Gledhill-Holmes, PhD Student, University of Central Florida,
4000 Central Florida Blvd, Orlando, FL, 32816, United States of
America, ruth_gledhill_holmes@yahoo.com, Ola Batarseh,
Dima Nazzal
3 - Collaborative Strategies for Traffic Management in the Airspace
Flow Program
Amy Kim, amykim0603@gmail.com, Mark Hansen
We investigate methods that aim to minimize the user-cost impact of a future AFP
that employs rerouting and ground delay. Methods are assessed using a simple flight
cost specification; the deterministic part represents flight costs known to the FAA,
while the stochastic part represents costs known only to the airline. Models
featuring different allocation schemes, user inputs, and timing of information gather
are compared. We explore tradeoffs between information quality and timeliness.
This research considers the possible service policy options necessary to extend and
maximize a product’s usable life (hence resulting in reduced production rates and
the associated environmental benefits of this) in conjunction with the possible
recovery options for maximizing the re-capture of end-of-use products (hence
resulting in reduced waste, reduced need for first-use materials, and recovery of
value for the manufacturer).
4 - Assessing the Impact of Stochastic Capacity Variation on
Coordinated Air Traffic Flow Management
Andrew Churchill, Graduate Research Assistant, University of
Maryland, 1173 Martin Hall, College Park, MD, 20742, United States
of America, churchil@umd.edu, David Lovell, Michael Ball
2 - Integrating Environmental Considerations into Pricing and
Production Planning Models
Dima Nazzal, Assistant Professor, University of Central Florida, 4000
Central Florida Blvd., Orlando, FL, 32816, United States of America,
dnazzal@mail.ucf.edu, Ali Bozorgi
In this research, an integer optimization model for coordination between air traffic
flow management initiatives and a three parameter characterization of resource
capacity are used to understand the effects of random capacity variations.
Employing the optimization model within a Monte Carlo simulation, the results
suggest that each of the three parameters characterizing capacity have marginally
increasing impacts over a wide range of conditions.
We propose and test a multi period optimization model that integrates the
environmental impact of a product into the production and pricing decisions. The
model considers the trade-off between economic and environmental objectives.
3 - A Model for Reverse Logistics Under Uncertainty
Theresa Barker, PhD, University of Washington, Box 352650, Seattle,
WA, 98115, United States of America, barkertj@u.washington.edu,
Zelda Zabinsky
Many mixed-integer linear programming models have been developed for reverse
logistics. These models typically require producers to make certain network design
decisions in advance, such as how to collect the return product and where to
perform testing. We present an integrated MILP model that combines high-level and
detailed network design decisions, along with chance-constrained programming to
analyze the tradeoffs between various network configurations.
454
■ WD72
WD74
3 - Decision Support for Urban Search and Rescue
Lisa (Lichun) Chen, lcchen@umd.edu, Elise Miller-Hooks
The urban search and rescue (USAR) team deployment problem seeks an optimal
deployment of USAR teams to disaster sites so as to maximize the expected number
of saved lives over the search and rescue period. A multistage stochastic program
that captures problem uncertainty and dynamics is presented. A column generationbased technique is proposed for its solution. The techniques is illustrated on a case
study involving the 2010 Haiti earthquake.
Facility Logistics Session: Warehouse Order Picking
Sponsored Session
Chair: Russell Meller, Hefley Professor of Logistics and Entrepreneurship,
University of Arkansas, 4207 Bell Engineering, Fayetteville, AR, 72701,
United States of America, rmeller@uark.edu
1 - Boosting Productivity in Multiple-Aisle Order-Picking by Cellular
Bucket Brigades
Yun Fong Lim, Assistant Professor, Singapore Management
University, 50 Stamford Road #04-01, Singapore, Singapore,
yflim@smu.edu.sg
4 - Using TRANSIMS for On-line Transportation System Management
During Emergencies
Adel Sadek, Associate Professor, University at Buffalo, the State
University of New York, 233 Ketter Hall, Buffalo, NY, 14260,
United States of America, asadek@buffalo.edu, Daniel Fuglewicz,
Alan Blatt, Yunjie Zhao
The topic of transportation systems management during emergencies has recently
received national attention. This study has two primary objectives: (1) to assess the
level to which the TRANSIMS model can be used for the online management of
transportation systems during emergencies; and (2) to develop any additional
functionality needed for that. As a case study, the research uses the Buffalo-Niagara
area known for its winter weather and numerous snow storms.
We introduce a new design of bucket brigades for order-picking in multiple, parallel
aisles. Workers pick products from one side of an aisle when they proceed in one
direction and they pick from the other side of the aisle, possibly for other customer
orders, when they proceed in the reverse direction. We assume hand-off times are
significant and propose simple rules for workers to share work. The new design can
be substantially more productive than traditional bucket brigades.
■ WD74
2 - Using Storage Profiles with Bucket Brigade Order Picking to
Improve Productivity
Don Eisenstein, Professor of Operations Management, University of
Chicago, Booth School of Business, 5807 South Woodlawn Avenue,
Chicago, IL, 60637, United States of America,
Don.Eisenstein@chicagobooth.edu, Yeming Gong
Joint Session TSL/ Service Science: Emergency
Transportation, Logistics, and Evacuation Service
Sponsor: Transportation Science and Logistics Society/
Service Science
Sponsored Session
We compare bucket brigade and zone order picking protocols using various storage
profiles. We find that the flexibility of a bucket brigade protocol can lead to some
considerable advantages in productivity.
Chair: Tao Yao, Assistant Professor, Pennsylvania State University, 349
Leonhard Building, University Park, PA, 16802, United States of America,
tyy1@engr.psu.edu
1 - Distributing Supplies in a Multi-city Infectious Disease Outbreak
Fernando Ordonez, Associate Professor, University of Southern
California, Department of Industrial and Systems Eng, 3715
McClintock Ave, Los Angeles, CA, 90007, United States of America,
fordon@usc.edu, Yingtao Ren
3 - Modeling the Throughput Performance of a Picking Machine OrderFulfillment Technology
Jennifer Pazour, PhD Candidate, University of Arkansas,
4207 Bell Engineering Center, Fayetteville, AR, 72701,
United States of America, jpazour@uark.edu, Russell Meller
Picking machines are an example of a stock-to-picker piece-level fulfillment
technology that consists of two or more pick stations, a common storage system,
and an integrated conveyor system. We develop a stability function model based on
queuing theory that is capable of determining if a picking machine will be able to
meet a throughput requirement. We then illustrate how a manager could use our
analytical model to answer picking machine design questions.
We consider the distribution of medicine to mitigate a multi-city infectious disease
outbreak under parameter uncertainty. We build a two-stage stochastic
programming model which has integer variables in both stages. This problem is
solved with a modified Bender’s method to recover dual information from the
second stage MIP and to speed up convergence. We illustrate the use of the model
and the algorithm in planning an emergency response to a hypothetical national
smallpox outbreak.
■ WD73
2 - Evacuation Planning Under Uncertainty: A Distributional Robust
Chance-Constrained Approach
Tao Yao, Assistant Professor, Pennsylvania State University, 349
Leonhard Building, University Park, PA, 16802, United States of
America, tyy1@engr.psu.edu, Byung Do Chung, Bo Zhang
Joint Session TSL/ SPPSN: Mitigating Disaster Impact
Through Planning for Emergency Response
Sponsored Session
This talk provides a Chance-constrained Programming approach for evacuation
transportation planning which are robust to uncertainty. We focus on demand
uncertainty with partial distributional information and develop an approximation
scheme to reformulate the problem as a deterministic convex program which is then
proved to be safe and computationally tractable. Numerical experiments are
provided to illustrate the performance of the proposed approach.
Chair: Elise Miller-Hooks, University of Maryland, 1173 Glenn Martin
Hall, College Park, MD, 20742, United States of America,
elisemh@umd.edu
1 - A Robust P-center Model for Emergency Facility Location Planning
Chung-Cheng Lu, Assistant Professor, National Taipei University of
Technology, 1 Section 3, Chung-Hsiao E. Road, Information and
Logistics Management, Taipei, 106, Taiwan - ROC,
jasoncclu@gmail.com
3 - Demand Management for Evacuation Planning
Douglas Bish, Assistant Professor, Grado Department of Industrial
and Systems Engineering, Virginia Tech, Blacksburg, VA, 24061,
United States of America, drb1@vt.edu
In hurricane evacuations traffic often overwhelms the infrastructure, causing
congestion that can increase the risk to the population. Supply management
strategies are used in evacuation planning, but they are often insufficient. We study
the use of demand management strategies that attempt to structure the evacuation
demand in order to minimize congestion. Specifically, we study network flow
problems that incorporate important aspects of evacuee behavior and evacuation
management issues.
This study deals with the p-center problem with uncertain travel times between
emergency facilities and affected areas which may arise in large-scale disasters. The
uncertain travel times are represented by intervals and a robust optimization
approach that minimizes the worst-case deviation from optimal solutions was
developed. Numerical experiments were conducted to demonstrate the effectiveness
of the approach and to examine the tradeoff between robustness and optimality.
2 - Locating Support Facilities for Large Scale Emergencies
Anurag Verma, Graduate Student, Texas A&M University, Industrial
and Systems Engineering, College Station, TX, 77843-3131,
United States of America, anuragverma@tamu.edu, Gary Gaukler
4 - Optimal Evacuation Routing Under Dynamic Stochastic Risks
Chi Xie, Research Fellow, The University of Texas at Austin, 1
University Station, Austin, TX, 78712, United States of America,
chi.xie@mail.utexas.edu, Tao Yao, Travis Waller
We provide large scale emergency facility location models that account for the
unavailability of a disaster response facility depending on its location and the
position of the disaster. We find that the locations suggested by the models in this
paper significantly reduce the expected cost of transportation of supplies when we
consider the damage a disaster causes to the support facilities and areas near it.
We propose a risk-based modeling framework and solution procedure for dynamic
evacuation planning under hazardous material releases, which integrates the latest
atmospheric dispersion modeling and network flow modeling techniques. A robust
dynamic evacuation routing model is presented for devising evacuation plans that
minimize the most risky exposure to the evacuating population under timedependent, uncertain hazardous effluents.
455

Wednesday

Transcription

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