Citations to Publications of Dr. Carlos A. Coello Coello that appear

Transcription

Citations to Publications of
Dr. Carlos A. Coello Coello
that appear in the ISI Web of Science.
The total of citations (excluding self-citations and citations from his co-authors)
is 5327.
Tesis Doctoral
• Carlos A. Coello Coello. An Empirical Study of Evolutionary Techniques for Multiobjective Optimization
in Engineering Design, PhD thesis, Department of Computer Science, Tulane University, New Orleans,
Louisiana, April 1996.
1. Ayeley P. Tchangani, “Considering Bipolarity of Attributes With Regards to Objectives in Decisions Evaluation”,
Inzinerine Ekonomika–Engineering Economics, Vol. 21, No. 5, pp. 475–484, 2010.
2. K. Metaxiotis and K. Liagkouras, “Multiobjective Evolutionary Algorithms for Portfolio Management: A comprehensive
literature review”, Expert Systems with Applications, Vol. 39, No. 14, pp. 11685–11698, October 15, 2012.
3. Musrrat. Ali, Patrick Siarry and Millie. Pant, “An efficient Differential Evolution based algorithm for solving multiobjective optimization problems”, European Journal of Operational Research, Vol. 217, No. 2, pp. 404–416, March 1,
2012.
4. Hamit Saruhan, “Pivoted-pad journal bearings lubrication design”, Industrial Lubrication and Tribology, Vol. 63, Nos.
2-3, pp. 119–126, 2011.
5. Mark A. Gammon, “Optimization of fishing vessels using a Multi-Objective Genetic Algorithm”, Ocean Engineering,
Vol. 38, No. 10, pp. 1054–1064, July 2011.
6. Cleber Zanchettin, Teresa B. Ludermir and Leandro Maciel Almeida, “Hybrid Training Method for MLP: Optimization
of Architecture and Training”, IEEE Transactions on Systems, Man, and Cybernetics Part B–Cybernetics, Vol. 41, No.
4, pp. 1097–1109, August 2011.
7. Min-Yuan Cheng and Ching-Shan Chen, “Optimal planning model for school buildings considering the tradeoff of seismic
resistance and cost effectiveness: a Taiwan case study”, Structural and Multidisciplinary Optimization, Vol. 43, No. 6,
pp. 863–879, June 2011.
8. Indika Meedeniya, Barbora Buhnova, Aldeida Aleti and Lars Grunske, “Reliability-driven deployment optimization for
embedded systems”, Journal of Systems and Software, Vol. 84, No. 5, pp. 835–846, May 2011.
9. S. Dhouib, A. Kharrat and H. Chabchoub, “Goal programming using multiple objective hybrid metaheuristic algorithm”,
Journal of the Operational Research Society, Vol. 62, No. 4, pp. 677–689, April 2011.
10. Souhail Dhouib, Aida Kharrat and Habib Chabchoub, “A multi-start threshold accepting algorithm for multiple objective
continuous optimization problems”, International Journal for Numerical Methods in Engineering, Vol. 83, No. 11, pp.
1498–1517, September 10, 2010.
11. C.A. Cortes, E. Mombello, R. Dib and G. Ratta, “A new class of flat-top windows for exposure assessment in magnetic
field measurements”, Signal Processing, Vol. 87, No. 9, pp. 2151–2164, September 2007.
12. Wahed Mohamed, Ibrahim Wesam and Effat Ahmed, “Finding an optimization of the plate element of Egyptian research
reactor using genetic algorithm”, Nuclear Science and Techniques, Vol. 19, No. 5, pp. 314–320, October 20, 2008.
13. Boguslaw Pytlak, “Multicriteria optimization of hard turning operation of the hardened 18HGT steel”, International
Journal of Advanced Manufacturing Technology, Vol. 49, Nos. 1–4, pp. 305–312, July 2010.
14. J. Dipama, A. Teyssedou, F. Aube and L. Lizon-A-Lugrin, “A grid based multi-objective evolutionary algorithm for the
optimization of power plants”, Applied Thermal Engineering, Vol. 30, Nos. 8-9, pp. 807–816, June 2010.
15. Zhi-Hua Hu, “A multiobjective immune algorithm based on a multiple-affinity model”, European Journal of Operational
Research, Vol. 202, No. 1, pp. 60–72, April 1, 2010.
16. Honglin Li, Hailei Zhang, Mingyue Zheng, Jie Luo, Ling Kang, Xiaofeng Liu, Xicheng Wang and Hualiang Jiang, “An
effective docking strategy for virtual screening based on multi-objective optimization algorithm”, BMC Bioinformatics,
Vol. 10, article number 58, February 11, 2009.
17. A. Albers, N. Leon-Rovira, H. Aguayo and T. Maier, “Development of an engine crankshaft in a framework of computeraided innovation”, Computers in Industry, Vol. 60, No. 8, pp. 604–612, October 2009.
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18. Mohamed El-Sayed Wahed, Wesam Zakaria Ibrahim and Ahmed Mostafa Effat, “Multiobjective Optimization of the
Plate Element of Egyptian Research Reactor Using Genetic Algorithm”, Nuclear Science and Engineering, Vol. 162, No.
3, pp. 275–281, July 2009.
19. Min-Rong Chen, Yong-zai Lu and Gen-ke Yang, “Multiobjective extremal optimization with applications to engineering
design”, Journal of Zhejiang University SCIENCE A, Vol. 8, No. 12, pp. 1905–1911, November 2007.
20. C. Elegbede, “Structural reliability assessment based on particles swarm optimization”, Structural Safety, Vol. 27, No.
2, pp. 171–186, 2005.
21. Adil Baykasoˇ
glu, “Preemptive goal programming using simulated annealing”, Engineering Optimization, Vol. 37, No. 1,
pp. 49–63, January 2005.
22. Guan-Chun Luh and Chung-Huei Chueh, “Multi-objective optimal design of truss structure with immune algorithm”,
Computers & Structures, Vol. 82, Nos. 11–12, pp. 829–844, May 2004.
23. J. Oh and C. Wu, “Genetic-algorithm-based real-time task scheduling with multiple goals”, Journal of Systems and
Software, Vol. 71, No. 3, pp. 245–258, May 2004.
24. C. Elegbede and K. Adjallah, “Availability allocation to repairable systems with genetic algorithms: a multi-objective
formulation”, Reliability Engineering & System Safety, Vol. 82, No. 3, pp. 319–330, December 2003.
25. Balram Suman, “Simulated Annealing-Based Multiobjective Algorithms and Their Application for System Reliability”,
Engineering Optimization, Vol. 35, No. 4, pp. 391–416, August 2003.
26. R.F. Coelho, H. Bersini and P. Bouillard, “Parametrical mechanical design with constraints and preferences: application
to a purge valve”, Computer Methods in Applied Mechanics and Engineering, Vol. 192, Nos. 39–40, pp. 4355–4378,
2003.
27. B. De Smedt and G.C.E. Gielen, “WATSON: Design space boundary exploration and model generation for analog and
RF IC design”, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, Vol. 22, No. 2, pp.
213–224, February 2003.
28. Johan Andersson and David Wallace, “Pareto optimization using the struggle genetic crowding algorithm”, Engineering
Optimization, Vol. 34, No. 6, pp. 623–643, December 2002.
29. Guan-Chun Luh, Chung-Huei Chueh and Wei-Wen Liu, “MOIA: Multi-Objective Immune Algorithm”, Engineering
Optimization, Volume 35, No. 2, pp. 143–164, April 2003.
30. K.C. Tan, E.F. Khor, T.H. Lee and Y.J. Yang, “A tabu-based exploratory evolutionary algorithm for multiobjective
optimization”, Artificial Intelligence Review, Vol. 19, No. 3, pp. 231–260, May 2003.
31. K.C. Tan, E.F. Khor, T.H. Lee and R. Sathikannan, “An evolutionary algorithm with advanced goal and priority
specification for multi-objective optimization”, Journal of Artificial Intelligence Research, Vol. 18, pp. 183–215, 2003.
32. K.C. Tan, T.H. Lee and E.F. Khor, “Evolutionary Algorithms for Multi-Objective Optimization: Performance Assessments and Comparisons”, Artificial Intelligence Review, Vol. 17, No. 4, pp. 253–290, June 2002.
33. K.C. Tan, T.H. Lee & E. F. Khor, “Evolutionary Algorithms with Dynamic Population Size and Local Exploration for
Multiobjective Optimization”, IEEE Transactions on Evolutionary Computation, Vol. 5, No. 6, pp. 565-588, December
2001.
34. A. Baykasoglu, “Goal programming using multiple objective tabu search”, Journal of the Operational Research Society,
Vol. 52, No. 12, pp. 1359–1369, December 2001.
35. K.C. Tan, Tong H. Lee, D. Khoo & E.F. Khor, “A Multiobjective Evolutionary Algorithm Toolbox for Computer-Aided
Multiobjective Optimization”, IEEE Transactions on Systems, Man, and Cybernetics—Part B: Cybernetics, Vol. 31,
No. 4, pp. 537–556, August 2001.
36. Johan Andersson and Peter Krus, “Multiobjective Optimization of Mixed Variable Design Problems”, en Eckart Zitzler,
Kalyanmoy Deb, Lothar Thiele, Carlos A. Coello Coello & David Corne (Eds.), First International Conference on
Evolutionary Multi-Criterion Optimization, Springer-Verlag, Zurich, Suiza, pp. 624–638, Marzo de 2001.
37. Matthias Ehrgott and Xavier Gandibleux, “A Survey and Annotated Bibliography of Multiobjective Combinatorial
Optimization”, OR Spektrum, Vol. 22, pp. 425–460, 2000.
38. B. Suman, “Study of self-stopping PDMOSA and performance measure in multiobjective optimization”, Computers &
Chemical Engineering, Vol. 29, No. 5, pp. 1131–1147, April 15, 2005.
39. J. Olvander, “Robustness considerations in multi-objective optimal design”, Journal of Engineering Design, Vol. 16, No.
5, pp. 511–523, October 2005.
40. M. Omran, A.P. Engelbrecht and A. Salman, “Particle swarm optimization method for image clustering”, International
Journal of Pattern Recognition and Artificial Intelligence, Vol. 19, No. 3, pp. 297–321, May 2005.
41. David Greiner, Gabriel Winter, José M. Emperador and Blas Galván, “Gray Coding in Evolutionary Multicriteria
Optimization: Application in Frame Structural Optimum Design”, in Carlos A. Coello Coello, Arturo Hern´
andez Aguirre
and Eckart Zitzler (editors), Evolutionary Multi-Criterion Optimization. Third International Conference, EMO 2005,
pp. 576–591, Springer. Lecture Notes in Computer Science Vol. 3410, Guanajuato, México, March 2005.
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42. Seyed Hamid Reza Pasandideh and Seyed Taghi Akhavan Niaki, “Multi-response simulation optimization using genetic
algorithm within desirability function framework”, Applied Mathematics and Computation, Vol. 175, No. 1, pp. 366–382,
April 1, 2006.
43. B. Suman and P. Kumar, “A survey of simulated annealing as a tool for single and multiobjective optimization”, Journal
of the Operational Research Society, Vol. 57, No. 10, pp. 1143–1160, October 2006.
Libros
• Carlos A. Coello Coello, David A. Van Veldhuizen and Gary B. Lamont, “Evolutionary Algorithms for Solving
Multi-Objective Problems”, Kluwer Academic Publishers, New York, USA, ISBN 0-3064-6762-3, May 2002.
o Carlos A. Coello Coello, Gary B. Lamont and David A. Van Veldhuizen, “Evolutionary Algorithms for
Solving Multi-Objective Problems”, Second Edition, Springer-Verlag, New York, USA, Septiembre 2007,
ISBN 978-0-387-33254-3.
1. Javier Rubio-Loyola, Gregorio Toscano-Pulido, Marinos Charalambides, Marisol Magana-Aguilar, Joan Serrat-Fernandez,
George Pavlou and Hiram Galeana-Zapien, “Business-driven policy optimization for service management”, International
Journal of Network Management, Vol. 25, No. 2, pp. 113–140, March-April 2015.
2. Alan R.R. de Freitas, Peter J. Fleming and Federico G. Guimaraes, “Aggregation Trees for visualization and dimension
reduction in many-objective optimization”, Information Sciences, Vol. 298, pp. 288–314, March 20, 2015.
3. Ana Belen Ruiz, Ruben Saborido and Mariano Luque, “A preference-based evolutionary algorithm for multiobjective
optimization: the weighting achievement scalarizing function genetic algorithm”, Journal of Global Optimization, Vol.
62, No. 1, pp. 101–129, May 2015.
4. Rui Wang, Robin C. Purshouse, Ioannis Giagkiozis and Peter J. Fleming, “The iPICEA-g: a new hybrid evolutionary
multi-criteria decision making approach using the brushing technique”, European Journal of Operational Research, Vol.
243, No. 2, pp. 442–453, June 1, 2015.
5. Xiaoguang He, Cai Dai and Zehua Chen, “Many-Objective Optimization Using Adaptive Differential Evolution with a
New Ranking Method”, Mathematical Problems in Engineering, Article Number: 259473, 2014.
6. Cai Dai, Yuping Wang and Miao Ye, “A new evolutionary algorithm based on contraction method for many-objective
optimization problems”, Applied Mathematics and Computation, Vol. 245, pp. 191–205, October 15, 2014.
7. A. Kaveh and K. Laknejadi, “A new multi-swarm multi-objective optimization method for structural design”, Advances
in Engineering Software, Vol. 58, pp. 54–69, April 2013.
8. Sanghamitra Bandyopadhyay, Rudrasis Chakraborty and Ujjwal Maulik, “Priority based epsilon dominance: A new
measure in multiobjective optimization”, Information Sciences, Vol. 305, pp. 97–109, June 1, 2015.
9. Ernestas Filatovas, Olga Kurasova and Karthik Sendhya, “Synchronous R-NSGA-II: An Extended Preference-Based
Evolutionary Algorithm for Multi-Objective Optimization”, Informatica, Vol. 26, No. 1, pp. 33–50, 2015.
10. Proteek Chandan Roy, Md. Monirul Islam, Kazuyuki Murase and Xin Yao, “Evolutionary Path Control Strategy for
Solving Many-Objective Optimization Problem”, IEEE Transactions on Cybernetics, Vol. 45, No. 4, pp. 702–715, April
2015.
11. Bili Chen, Wenhua Zeng, Yangbin Lin and Defu Zhang, “A New Local Search-Based Multiobjective Optimization
Algorithm”, IEEE Transactions on Evolutionary Computation, Vol. 19, No. 1, pp. 50–73, February 2015.
12. Hossein Rajabalipour Cheshmehgaz, Mohammad Ishak Desa and Antoni Wibowo, “Effective local evolutionary searches
distributed on an island model solving bi-objective optimization problems”, Applied Intelligence, Vol. 38, No. 3, pp.
331–356, April 2013.
13. Bernabe Dorronsoro, Gregoire Danoy, Antonio J. Nebro and Pascal Bouvry, “Achieving super-linear performance in parallel multi-objective evolutionary algorithms by means of cooperative coevolution”, Computers & Operations Research,
Vol. 40, No. 6, pp. 1552–1563, June 2013.
14. Mohammad Mortazavi-Naeini, George Kuczera and Lijie Cui, “Efficient multi-objective optimization methods for computationally intensive urban water resources models”, Journal of Hydroinformatics, Vol. 17, No. 1, pp. 36–55, 2015.
15. J¨
urgen Branke, Salvatore Greco, Roman Slowinski and Piotr Zielniewicz, “Learning Value Functions in Interactive
Evolutionary Multiobjective Optimization”, IEEE Transactions on Evolutionary Computation, Vol. 19, No. 1, pp.
88–102, February 2015.
16. Yong Zhang, Dun-Wei Gong and Na Gong, “Multi-Objective Optimization Problems Using Cooperative Evolvement
Particle Swarm Optimizer”, Journal of Computational and Theoretical Nanoscience, Vol. 10, No. 3, pp. 655-663, March
2013.
17. Matthew P. Ferringer, Ronald S. Clifton and Timothy G. Thompson, “Efficient and accurate evolutionary multi-objective
optimization paradigms for satellite constellation design”, Journal of Spacecraft and Rockets, Vol. 44, No. 3, pp. 682–691,
May-June 2007.
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18. Han-Young Park, Akhil Datta-Gupta and Michael J. King, “Handling conflicting multiple objectives using Pareto-based
evolutionary algorithm during history matching of reservoir performance”, Journal of Petroleum Science and Engineering,
Vol. 125, pp. 48–66, January 2015.
19. Jianhua Xiao, Jin Xu, Xiutang Geng and Linqiang Pan, “Multi-objective carrier chaotic evolutionary algorithm for DNA
sequences design”, Progress in Natural Science, Vol. 17, No. 12, pp. 1515–1520, December 2007.
20. Juan Rada-Vilela, Manuel Chica, Oscar Cordon and Sergio Damas, “A comparative study of Multi-Objective Ant Colony
Optimization algorithms for the Time and Space Assembly Line Balancing Problem”, Applied Soft Computing, Vol. 13,
No. 11, pp. 4370–4382, November 2013.
21. Jinn-Tsong Tsai, Ching-I. Yang and Jyh-Horng Chou, “Hybrid sliding level Taguchi-based particle swarm optimization
for flowshop scheduling problems”, Applied Soft Computing, Vol. 15, pp. 177–192, February 2014.
22. Hossein Rajabalipour Cheshmehgaz, Habibollah Haron and Abdollah Sharifi, “The review of multiple evolutionary
searches and multi-objective evolutionary algorithms”, Artificial Intelligence Review, Vol. 43, No. 3, pp. 311–343,
March 2015.
23. Jonathan E. Fieldsend and Richard M. Everson, “The Rolling Tide Evolutionary Algorithm: A Multiobjective Optimizer
for Noisy Optimization Problems”, IEEE Transactions on Evolutionary Computation, Vol. 19, No. 1, pp. 103–117,
February 2015.
24. Gideon Avigad, Alex Goldvard and Shaul Salomon, “Time-response-based evolutionary optimization”, Engineering
Optimization, Vol. 47, No. 4, pp. 533–549, April 3, 2015.
25. Prakash Shelokar, Arnaud Quirin and Oscar Cordon, “Three-objective subgraph mining using multiobjective evolutionary
programming”, Journal of Computer and System Sciences, Vol. 80, No. 1, pp. 16–26, February 2014.
26. Miguel Porto, Otilia Correia and Pedro Beja, “Optimization of Landscape Services under Uncoordinated Management
by Multiple Landowners”, Plos One, Vol. 9, No. 1, Article Number: e86001, January 17, 2014.
27. Xue-Song Yang, Bing-Zhong Wang, Sai Ho Yeung, Quan Xue and Kim Fung Man, “Circularly Polarized Reconfigurable
Crossed-Vagi Patch Antenna”, IEEE Antennas and Propagation Magazine, Vol. 53, No. 5, pp. 65–80, October 2011.
28. Ming Zhai, Changyu Shen, Chuntai Liu and Jingbo Chen, “Optimization of runner sizes and process conditions considering both part quality and manufacturing cost in injecting molding”, Journal of Polymer Engineering, Vol. 31, Nos.
6-7, pp. 489–494, November 2011.
29. Wesley Klewerton Guez Assuncao, Thelma Elita Colanzi, Silvia Regina Vergilio and Aurora Pozo, “A multi-objective
optimization approach for the integration and test order problem”, Information Sciences, Vol. 267, pp. 119–139, May
20, 2014.
30. Krishnaswamy Hariharan, Nirupam Chakraborti, Frederic Barlat and Myoung-Gyu Lee, “A Novel Multi-objective Genetic Algorithms-Based Calculation of Hill’s Coefficients”, Metallurgical and Materials Transactions A–Physical Metallurgy and Materials Science, Vol. 45A, No. 6, pp. 2704–2707, June 2014.
31. Miqing Li, Shengxiang Yang, Jinhua Zheng and Xiaohui Liu, “ETEA: A Euclidean Minimum Spanning Tree-Based
Evolutionary Algorithm for Multi-Objective Optimization”, Evolutionary Computation, Vol. 22, No. 2, pp. 189–230,
Summer 2014.
32. Khairy Elsayed and Chris Lacor, “ Robust parameter design optimization using Kriging, RBF and RBFNN with gradientbased and evolutionary optimization techniques”, Applied Mathematics and Computation, Vol. 236, pp. 325–344, June
1, 2014.
33. Lianbo Ma, Kunyuan Hu, Yunlong Zhu and Hanning Chen, “Cooperative artificial bee colony algorithm for multiobjective RFID network planning”, Journal of Network and Computer Applications, Vol. 42, pp. 143–162, June 2014.
34. Ehsan Gholamalizadeh and Man-Hoe Kim, “Thermo-economic triple-objective optimization of a solar chimney power
plant using genetic algorithms”, Energy, Vol. 70, pp. 204–211, June 1, 2014.
35. Miqing Li, Shengxiang Yang and Xiaohui Liu, “Diversity Comparison of Pareto Front Approximations in Many-Objective
Optimization”, IEEE Transactions on Cybernetics, Vol. 44, No. 12, pp. 2568–2584, December 2014.
36. Huseyin Onur Mete and Zelda B. Zabinsky, “Multiobjective Interacting Particle Algorithm for Global Optimization”,
INFORMS Journal on Computing, Vol. 26, No. 3, pp. 500–513, Summer 2014.
37. Kostas Florios and George Mavrotas, “Generation of the exact Pareto set in Multi-Objective Traveling Salesman and
Set Covering Problems”, Applied Mathematics and Computation, Vol. 237, pp. 1–19, June 15, 2014.
38. Enze Zhang, Yifei Wu and Qingwei Chen, “ A practical approach for solving multi-objective reliability redundancy
allocation problems using extended bare-bones particle swarm optimization”, Reliability Engineering & System Safety,
Vol. 127, pp. 65–76, July 2014.
39. S. Sinaie, A. Heidarpour and X.L. Zhao, “A multi-objective optimization approach to the parameter determination of
constitutive plasticity models for the simulation of multi-phase load histories”, Computers & Structures, Vol. 138, pp.
112–132, July 1, 2014.
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40. Jose D. Martinez-Morales, Elvia R. Palacios-Hernandez and Gerardo A. Velazquez-Carrillo, “Artificial neural network
based on genetic algorithm for emissions prediction of a SI gasoline engine”, Journal of Mechanical Science and Technology, Vol. 28, No. 6, pp. 2417–2427, June 2014.
41. Yangyang Li, Xia Xu, Peidao Li and Licheng Jiao, “Improved RM-MEDA with local learning”, Soft Computing, Vol.
18, No. 7, pp. 1383–1397, July 2014.
42. I. Montalvo, J. Izquierdo, R. Perez-Garcia and M. Herrera, “Water Distribution System Computer-Aided Design by
Agent Swarm Optimization”, Computer-Aided Civil and Infrastructure Engineering, Vol. 29, No. 6, pp. 433–448, July
2014.
43. You-Jin Park, Rong Pan, Connie M. Borror, Douglas C. Montgomery and Gyu-Bong Lee, “Simultaneous Improvement
of Energy Efficiency and Product Quality in PCB Lamination Process”, International Journal of Precision Engineering
and Manufacturing–Green Technology, Vol. 1, No. 3, pp. 247–256, July 2014.
44. Weijian Kong, Tianyou Chai, Jinliang Ding and Shengxiang Yang, “Multifurnace Optimization in Electric Smelting
Plants by Load Scheduling and Control”, IEEE Transactions on Automation Science and Engineering, Vol. 11, No. 3,
pp. 850–862, July 2014.
45. Kamal Boudjelaba, Frederic Ros and Djamel Chikouche, “Adaptive genetic algorithm-based approach to improve the
synthesis of two-dimensional finite impulse response filters”, IET Signal Processing, Vol. 8, No. 5, pp. 429–446, July
2014.
46. Michele Amoretti, “Evolutionary strategies for ultra-large-scale autonomic systems”, Information Sciences, Vol. 274,
pp. 1–16, August 1, 2014.
47. Julien Schleich, Gregoire Danoy, Bernabe Dorronsoro and Pascal Bouvry, “Optimising small-world properties in VANETs:
Centralised and distributed overlay approaches”, Applied Soft Computing, Vol. 21, pp. 637–646, August 2014.
48. Danial S. Mohammadzadeh, Jafar Bolouri Bazaz and Amir H. Alavi, “An evolutionary computational approach for
formulation of compression index of fine-grained soils”, Engineering Applications of Artificial Intelligence, Vol. 33, pp.
58–68, August 2014.
49. Masoud Sharafi and Tarek Y. ELMekkawy, “Multi-objective optimal design of hybrid renewable energy systems using
PSO-simulation based approach”, Renewable Energy, Vol. 68, pp. 67–79, August 2014.
50. Mehmet Unal and Gordon P. Warn, “Optimal cost-effective topology of column bearings for reducing vertical acceleration
demands in multistory base-isolated buildings”, Earthquake Engineering & Structural Dynamics, Vol. 43, No. 8, pp.
1107–1127, July 10, 2014.
51. Zulkifli Mohamed, Mitsuki Kitani, Shin-ichiro Kaneko and Genci Capi, “Humanoid robot arm performance optimization
using multi objective evolutionary algorithm”, International Journal of Control Automation and Systems, Vol. 12, No.
4, pp. 870–877, August 2014.
52. David Gonzalez, Mario Garcia-Lozano, Silvia Ruiz and Dong Seop Lee, “A metaheuristic-based downlink power allocation
for LTE/LTE-A cellular deployments”, Wireless Networks, Vol. 20, No. 6, pp. 1369–1386, August 2014.
53. Himanshu Jain and Kalyanmoy Deb, “An Evolutionary Many-Objective Optimization Algorithm Using Reference-Point
Based Nondominated Sorting Approach, Part II: Handling Constraints and Extending to an Adaptive Approach”, IEEE
Transactions on Evolutionary Computation, Vol. 18, No. 4, pp. 602–622, August 2014.
54. Sepehr Sanaye and Navid Khakpaay, “Simultaneous use of MRM (maximum rectangle method) and optimization methods
in determining nominal capacity of gas engines in CCHP (combined cooling, heating and power) systems”, Energy, Vol.
72, pp. 145–158, August 1, 2014.
55. Vijay Rathod, Om Prakash Yadav, Ajay Rathore and Rakesh Jain, “Optimizing reliability-based robust design model
using multi-objective genetic algorithm”, Computers & Industrial Engineering, Vol. 66, No. 2, pp. 301–310, October
2013.
56. Jie Tang, Daniel K.C. So, Emad Alsusa and Khairi Ashour Hamdi, “Resource Efficiency: A New Paradigm on Energy
Efficiency and Spectral Efficiency Tradeoff”, IEEE Transactions on Wireless Communications, Vol. 13, No. 8, pp.
4656–4669, August 2014.
57. Brian J. Ross, “The evolution of higher-level biochemical reaction models”, Genetic Programming and Evolvable Machines, Vol. 13, No. 1, pp. 3–31, March 2012.
58. S. Sharma, G.P. Rangaiah and K.S. Cheah, “Multi-objective optimization using MS Excel with an application to design
of a falling-film evaporator system”, Food and Bioproducts Processing, Vol. 90, No. C2, pp. 123–134, April 2012.
59. G. Ridolfi, E. Mooij, D. Cardile, S. Corpino and G. Ferrari, “A methodology for system-of-systems design in support of
the engineering team”, Acta Astronautica, Vol. 73, pp. 88–99, April-May 2012.
60. Chun-Hao Chen, Tzung-Pei Hong and Vincent S. Tseng, “Finding Pareto-front Membership Functions in Fuzzy Data
Mining”, International Journal of Computational Intelligence Systems, Vol. 5, No. 2, pp. 343–354, April 2012.
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61. Antonio A. Marquez, Francisco A. Marquez and Antonio Peregrin, “A Mechanism to Improve the Interpretability of
Linguistic Fuzzy Systems with Adaptive Defuzzification based on the use of a Multi-objective Evolutionary Algorithm”,
International Journal of Computational Intelligence Systems, Vol. 5, No. 2, pp. 297–321, April 2012.
62. Laszlo Daroczy, Gabor Janiga and Dominique Thevenin, “Systematic analysis of the heat exchanger arrangement problem
using multi-objective genetic optimization”, Energy, Vol. 65, pp. 364–373, February 1, 2014.
63. Dongdong Yang, Licheng Jiao, Ruican Niu and Maoguo Gong, “Investigation of Combinational Clustering Indices in
Artificial Immune Multi-Objective Clustering”, Computational Intelligence, Vol. 30, No. 1, pp. 115–144, February 2014.
64. Manojkumar Ramteke and Santosh K. Gupta, “Biomimetic Adaptations of GA and SA for the Robust MO Optimization
of an Industrial Nylon-6 Reactor”, Materials and Manufacturing Processes, Vol. 24, No. 1, pp. 38–46, Article Number:
PII 906599196, 2009.
65. Mohammad H. Kurdi, Tony L. Schmitz, Raphael T. Haftka and Brian P. Mann, “Milling optimisation of removal rate
and accuracy with uncertainty: Part 1: parameter selection”, International Journal of Materials & Product Technology,
Vol. 35, Nos. 1-2, pp. 3–25, 2009.
66. Gilbert Reynoso-Meza, Xavier Blasco, Javier Sanchis and Miguel Martinez, “Controller tuning using evolutionary multiobjective optimisation: Current trends and applications”, Control Engineering Practice, Vol. 28, pp. 58–73, July 2014.
67. Mei-Po Kwan, Ningchuan Xiao and Guoxiang Ding, “Assessing Activity Pattern Similarity with Multidimensional Sequence Alignment Based on a Multiobjective Optimization Evolutionary Algorithm”, Geographical Analysis, Vol. 46,
No. 3, pp. 297–320, July 2014.
68. Carlos R. Garcia-Alonso, Leonor M. Perez-Naranjo and Juan C. Fernandez-Caballero, “Multiobjective evolutionary
algorithms to identify highly autocorrelated areas: the case of spatial distribution in financially compromised farms”,
Annals of Operations Research, Vol. 219, No. 1, pp. 187–202, August 2014.
69. Francesco Folino and Clara Pizzuti, “An Evolutionary Multiobjective Approach for Community Discovery in Dynamic
Networks”, IEEE Transactions on Knowledge and Data Engineering, Vol. 26, No. 8, pp. 1838–1852, August 2014.
70. Joseph R. Kasprzyk, Patrick M. Reed, Gregory W. Characklis and Brian R. Kirsch, “Many-objective de Novo water
supply portfolio planning under deep uncertainty”, Environmental Modelling & Software, Vol. 34, pp. 87–104, June
2012.
71. Joseph R. Kasprzyk, Shanti Nataraj, Patrick M. Reed and Robert J. Lempert, “Many objective robust decision making
for complex environmental systems undergoing change”, Environmental Modelling & Software, Vol. 42, pp. 55–71, April
2013.
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distance based broadcasting protocol for MANETs”, Journal of Supercomputing, Vol. 62, No. 3, pp. 1213–1240,
December 2012.
299. I. Arnaldo, J.L. Risco-Martin, J.L. Ayala and J.I. Hidalgo, “Power profiling-guided floorplanner for 3D multi-processor
systems-on-chip”, IET Circuits Devices & Systems, Vol. 6, No. 5, pp. 322–329, September 2012.
300. Gift Dumedah, “Formulation of the Evolutionary-Based Data Assimilation, and its Implementation in Hydrological
Forecasting”, Water Resources Management, Vol. 26, No. 13, pp. 3853–3870, October 2012.
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301. Clare Levene, Elon Correa, Ewan W. Blanch and Royston Goodacre, “Enhancing Surface Enhanced Raman Scattering
(SERS) Detection of Propranolol with Multiobjective Evolutionary Optimization”, Analytical Chemistry, Vol. 84, No.
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302. Kalyanmoy Deb, Francisco Ruiz, Mariano Luque, Rahul Tewari, Jose M. Cabello and Jose M. Cejudo, “On the sizing of
a solar thermal electricity plant for multiple objectives using evolutionary optimization”, Applied Soft Computing, Vol.
12, No. 10, pp. 3300–3311, October 2012.
303. Gift Dumedah, Aaron A. Berg and Mark Wineberg, “Pareto-optimality and a search for robustness: choosing solutions
with desired properties in objective space and parameter space”, Journal of Hydroinformatics, Vol. 14, No. 2, pp.
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304. James N. Richardson, Sigrid Adriaenssens, Philippe Bouillard and Rajan Filomeno Coelho, “Multiobjective topology
optimization of truss structures with kinematic stability repair”, Structural and Multidisciplinary Optimization, Vol. 46,
No. 4, pp. 513–532, October 2012.
305. Chun-Hao Chen, Tzung-Pei Hong, Vincent S. Tseng and Lien-Chin Chen, “Multi-objective Genetic-Fuzzy Data Mining”,
International Journal of Innovative Computing Information and Control, Vol. 8, No. 10A, pp. 6551–6568, October 2012.
306. P.M. Mateo and I. Alberto, “A mutation operator based on a Pareto ranking for multi-objective evolutionary algorithms”,
Journal of Heuristics, Vol. 18, No. 1, pp. 53–89, February 2012.
307. M.R. Dashtbayazi, “Artificial Neural Network-Based Multiobjective Optimization of Mechanical Alloying Process for
Synthesizing of Metal Matrix Nanocomposite Powder”, Materials and Manufacturing Processes, Vol. 27, No. 1, pp.
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308. H. Nasiraghdam and S. Jadid, “Optimal hybrid PV/WT/FC sizing and distribution system reconfiguration using multiobjective artificial bee colony (MOABC) algorithm”, Solar Energy, Vol. 86, No. 10, pp. 3057–3071, October 2012.
309. Aryeh Warmflash, Paul Francois and Eric D. Siggia, “Pareto evolution of gene networks: an algorithm to optimize
multiple fitness objectives”, Physical Biology, Vol. 9, No. 5, Article Number: 056001, October 2012.
310. Manuel Chica, Oscar Cordon, Sergio Damas and Joaquin Bautista, “Multiobjective memetic algorithms for time and
space assembly line balancing”, Engineering Applications of Artificial Intelligence, Vol. 25, No. 2, pp. 254–273, March
2012.
311. E. Zio, L.R. Golea and C.M. Rocco, “Identifying groups of critical edges in a realistic electrical network by multi-objective
genetic algorithms”, Reliability Engineering & System Safety, Vol. 99, pp. 172–177, March 2012.
312. G. Chiandussi, M. Codegone, S. Ferrero and F.E. Varesio, “Comparison of multi-objective optimization methodologies
for engineering applications”, Computers & Mathematics with Applications, Vol. 63, No. 5, pp. 912–942, March 2012.
313. Nuno F. Lages, Carlos Cordeiro, Marta Sousa Silva, Ana Ponces Freire and Antonio E.N. Ferreira, “Optimization of
Time-Course Experiments for Kinetic Model Discrimination”, Plos One, Vol. 7, No. 3, Article Number: e32749, March
5, 2012.
314. Samane Noori-Darvish, Iraj Mahdavi and Nezam Mahdavi-Amiri, “A bi-objective possibilistic programming model for
open shop scheduling problems with sequence-dependent setup times, fuzzy processing times, and fuzzy due dates”,
Applied Soft Computing, Vol. 12, No. 4, pp. 1399–1416, April 2012.
315. Sahar Ashayer, Mansur Askari and Hossein Afarideh, “Optimal per cent by weight of elements in diagnostic quality
radiation shielding materials”, Radiation Protection Dosimetry, Vol. 149, No. 3, pp. 268–288, April 2012.
316. Manojkumar Ramteke and Rajagopalan Srinivasan, “Large-Scale Refinery Crude Oil Scheduling by Integrating Graph
Representation and Genetic Algorithm”, Industrial & Engineering Chemistry Research, Vol. 51, No. 14, pp. 5256–5272,
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317. Izaskun Ibarbia, Alexander Mendiburu, Maria Santos and Jose A. Lozano, “An interactive optimization approach to a
real-world oceanographic campaign planning problem”, Applied Intelligence, Vol. 36, No. 3, pp. 721–734, April 2012.
318. Weiqin Ying, Xing Xu, Yuxiang Feng and Yu Wu, “An Efficient Conical Area Evolutionary Algorithm for Bi-objective Optimization”, IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences, Vol. E95A,
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319. Roberto Santana, Concha Bielza and Pedro Larra˜
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321. Jun-fang Li, Bu-han Zhang, Yi-fang Liu, Kui Wang and Xiao-shan Wu, “Spatial evolution character of multi-objective
evolutionary algorithm based on self-organized criticality theory”, Physica A–Statistical Mechanics and its Applications,
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322. Ofer M. Shir, Jonathan Roslund, Zaki Leghtas and Herschel Rabitz, “Quantum control experiments as a testbed for
evolutionary multi-objective algorithms”, Genetic Programming and Evolvable Machines, Vol. 13, No. 4, pp. 445–491,
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323. Domenico A. Bau and Jonghyun Lee, “Multi-Objective Optimization for the Design of Groundwater Supply Systems
under Uncertain Parameter Distribution”, Pacific Journal of Optimization, Vol. 7, No. 3, pp. 407–424, September 2011.
324. Hugo-Tiago C. Pedro and Marcelo H. Kobayashi, “On a cellular division method for topology optimization”, International
Journal for Numerical Methods in Engineering, Vol. 88, No. 11, pp. 1175–1197, December 16, 2011.
325. Domenico A. Bau, “Planning of Groundwater Supply Systems Subject to Uncertainty Using Stochastic Flow Reduced
Models and Multi-Objective Evolutionary Optimization”, Water Resources Management, Vol. 26, No. 9, pp. 2513–2536,
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326. Anthony Gerard Scanlan and Mark Keith Halton, “Hierarchical synthesis system with hybrid DLO-MOGA optimization”,
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327. Gustavo Olague and Leonardo Trujillo, “Interest point detection through multiobjective genetic programming”, Applied
Soft Computing, Vol. 12, No. 8, pp. 2566–2582, August 2012.
328. A. Clarke and J.C. Miles, “Strategic Fire and Rescue Service decision making using evolutionary algorithms”, Advances
in Engineering Software, Vol. 50, pp. 29–36, August 2012.
329. Vicent Romero-Garcia, Juan Sanchez-Perez and Luis Miguel Garcia-Raffi, “Molding the Acoustic Attenuation in QuasiOrdered Structures: Experimental Realization”, Applied Physics Express, Vol. 5, No. 8, Article Number: 087301,
August 2012.
330. Pankaj Rajak, Sudipto Ghosh, Baidurya Bhattacharya and Nirupam Chakraborti, “Pareto-optimal analysis of Zn-coated
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September 2012.
331. Benedicte Quilot-Turion, Mohamed-Mahmoud Ould-Sidi, Abdeslam Kadrani, Nadine Hilgert, Michel Genard and Francoise Lescourret, “Optimization of parameters of the ‘Virtual Fruit’ model to design peach genotype for sustainable
production systems”, European Journal of Agronomy, Vol. 42, pp. 34–48, October 2012.
332. David Hadka and Patrick Reed, “Diagnostic Assessment of Search Controls and Failure Modes in Many-Objective
Evolutionary Optimization”, Evolutionary Computation, Vol. 20, No. 3, pp. 423–452, Fall 2012.
333. Anne Auger, Johannes Bader, Dimo Brockhoff and Eckart Zitzler, “Hypervolume-based multiobjective optimization:
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2012.
334. Wali Khan Mashwani and Abdellah Salhi, “A decomposition-based hybrid multiobjective evolutionary algorithm with
dynamic resource allocation”, Applied Soft Computing, Vol. 12, No. 9, pp. 2765–2780, September 2012.
335. F.R.B. Cruz, G. Kendall, L. While, A.R. Duarte and N.L.C. Brito, “Throughput Maximization of Queueing Networks
with Simultaneous Minimization of Service Rates and Buffers”, Mathematical Problems in Engineering, Article Number:
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336. Rodrigo Coelho Barros, Marcio Porto Basgalupp, Andre C.P.L.F. de Carvalho and Alex A. Freitas, “A Survey of
Evolutionary Algorithms for Decision-Tree Induction”, IEEE Transactions on Systems, Man and Cybernetics Part C–
Applications and Reviews, Vol. 42, No. 3, pp. 291–312, May 2012.
337. Reinhard Koenig and Sven Schneider, “Hierarchical structuring of layout problems in an interactive evolutionary layout
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338. Clara Pizzuti, “A Multiobjective Genetic Algorithm to Find Communities in Complex Networks”, IEEE Transactions
on Evolutionary Computation, Vol. 16, No. 3, pp. 418–430, June 2012.
339. Amelia Zafra and Sebastian Ventura, “Multi-objective approach based on grammar-guided genetic programming for
solving multiple instance problems”, Soft Computing, Vol. 16, No. 6, pp. 955–977, June 2012.
340. Kaveh Khalili-Damghani abnd Maghsoud Amiri, “Solving binary-state multi-objective reliability redundancy allocation
series-parallel problem using efficient epsilon-constraint, multi-start partial bound enumeration algorithm, and DEA”,
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341. Davide Bianchi, Simone Genovesi and Agostino Monorchio, “Constrained Pareto Optimization of Wide Band and Steerable Concentric Ring Arrays”, IEEE Transactions on Antennas and Propagation, Vol. 60, No. 7, pp. 3195–3204, July
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342. Renan S. Maciel, Mauro Rosa, Vladimiro Miranda and Antonio Padilha-Feltrin, “Multi-objective evolutionary particle
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343. Satoshi Kitayama and Koetsu Yamazaki, “Compromise point incorporating trade-off ratio in multi-objective optimization”, Applied Soft Computing, Vol. 12, No. 8, pp. 1959–1964, August 2012.
344. Manuel Cruz-Ramirez, Cesar Hervas-Martinez, Juan Carlos Fernandez, Javier Briceno and Manuel de la Mata, “Multiobjective evolutionary algorithm for donor-recipient decision system in liver transplants”, European Journal of Operational Research, Vol. 222, No. 2, pp. 317–327, October 16, 2012.
345. C. Voglis, K.E. Parsopoulos, D.G. Papageorgiou, I.E. Lagaris and M.N. Vrahatis, “MEMPSODE: A global optimization
software based on hybridization of population-based algorithms and local searches”, Computer Physics Communications,
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346. C. Fernandes, A.J. Pontes, J.C. Viana and A. Gaspar-Cunha, “Using Multi-objective Evolutionary Algorithms for
Optimization of the Cooling System in Polymer Injection Molding”, International Polymer Processing, Vol. 27, No. 2,
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347. Gheorghe Serban, Laurentiu Ionescu and Alin Mazare, “The Possibility of Optimisation for Power Supply Consumption
using Evolvable Power Regulator”, Revue Roumaine des Sciences Techniques–Serie Electrotechnique et Energetique, Vol.
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348. Fangqing Gu, Hai-lin Liu and Kay Chen Tan, “A Multiobjective Evolutionary Algorithm using Dynamic Weight Design
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349. Gilberto Reynoso-Meza, Javier Sanchis, Xavier Blasco and Juan M. Herrero, “Multiobjective evolutionary algorithms
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350. Youcef Bouchebaba, Ali-Erdem Ozcan, Pierre Paulin and Gabriela Nicolescu, “MpAssign: a framework for solving the
many-core platform mapping problem”, Software–Practice & Experience, Vol. 42, No. 7, pp. 891–915, July 2012.
351. Yakoub Bazi, Naif Alajlan and Farid Melgani, “Improved Estimation of Water Chlorophyll Concentration With Semisupervised Gaussian Process Regression”, IEEE Transactions on Geoscience and Remote Sensing, Vol. 50, No. 7, pp.
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352. Gustavo Olague and Leonardo Trujillo, “Interest point detection through multiobjective genetic programming”, Applied
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353. Ying Liu, Melody Kiang and Michael Brusco, “A unified framework for market segmentation and its applications”,
Expert Systems with Applications, Vol. 39, No. 11, pp. 10292–10302, September 1, 2012.
355. Federico Divina, Beatriz Pontes, Raul Giraldez and Jesus S. Aguilar-Ruiz, “An effective measure for assessing the quality
of biclusters”, Computers in Biology and Medicine, Vol. 42, No. 2, pp. 245–256, February 2012.
356. Massimo Vecchio, Roberto Lopez-Valcarce and Francesco Marcelloni, “A two-objective evolutionary approach based on
topological constraints for node localization in wireless sensor networks”, Applied Soft Computing, Vol. 12, No. 7, pp.
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357. Krzysztof Trawinski, Oscar Cordon and Arnaud Quirin, “A Study on the Use of Multiobjective Genetic Algorithms
for Classifier Selection in FURIA-based Fuzzy Multiclassifiers”, International Journal of Computational Intelligence
Systems, Vol. 5, No. 2, pp. 231–253, April 2012.
358. El-Ghazali Talbi, Matthieu Basseur, Antonio J. Nebro and Enrique Alba, “Multi-objective optimization using metaheuristics: non-standard algorithms”, International Transactions in Operational Research, Vol. 19, Nos. 1-2, pp. 283–
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359. Helon Vicente Hultmann Ayala and Leandro dos Santos Coelho, “Tuning of PID controller based on a multiobjective
genetic algorithm applied to a robotic manipulator”, Expert Systems with Applications, Vol. 39, No. 10, pp. 8968–8974,
August 2012.
360. Dedi Liu, Shenglian Guo, Xiaohong Chen, Quanxi Shao, Qihua Ran, Xingyuan Song and Zhaoli Wang, “A macroevolutionary multi-objective immune algorithm with application to optimal allocation of water resources in Dongjiang
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2012.
361. Yong Zhang, Dun-Wei Gong and Zhonghai Ding, “A bare-bones multi-objective particle swarm optimization algorithm
for environmental/economic dispatch”, Information Sciences, Vol. 192, pp. 213–227, June 1, 2012.
362. A. Weber, S. Fasoulas and K. Wolf, “Conceptual interplanetary space mission design using multi-objective evolutionary
optimization and design grammars”, Proceedings of the Institution of Mechanical Engineers Part G–Journal of Aerospace
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363. I.G.P. Asto Buditjahjanto and Hajime Miyauchi, “An Intelligent Decision Support Based on a Subtractive Clustering and
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364. A. Kaveh and K. Laknejadi, “A Hybrid Multi-Objective Optimization and Decision Making Procedure for Optimal
Design of Truss Structures”, Iranian Journal of Science and Technology–Transactions of Civil Engineering, Vol. 35, No.
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365. Juan J. Durillo and Antonio J. Nebro, “jMetal: A Java framework for multi-objective optimization”, Advances in
Engineering Software, Vol. 42, No. 10, pp. 760–771, October 2011.
366. Reza Akbari and Koorush Ziarati, “Multi-objective Bee Swarm Optimization”, International Journal of Innovative
Computing Information and Control, Vol. 8, No. 1B, pp. 715–726, January 2012.
367. Ali Kaveh, Karim Laknejadi and Babak Alinejad, “Performance-based multi-objective optimization of large steel structures”, Acta Mechanica, Vol. 223, No. 2, pp. 355–369, February 2012.
368. Khaled Badran and Peter Rockett, “Multi-class pattern classification using single, multi-dimensional feature-space feature
extraction evolved by multi-objective genetic programming and its application to network intrusion detection”, Genetic
Programming and Evolvable Machines, Vol. 13, No. 1, pp. 33–63, March 2012.
369. B. Naujoks, H. Trautmann, S. Wessing and C. Weihs, “Advanced concepts for multi-objective evolutionary optimization
in aircraft industry”, Proceedings of the Institution of Mechanical Engineers Part G–Journal of Aerospace Engineering,
Vol. 225, No. G10, pp. 1081–1096, October 2011.
370. Chiu-Hung Chen, Tung-Kuan Liu, I-Ming Huang and Jyh-Horng Chou, “Multiobjective Synthesis of Six-bar Mechanisms
Under Manufacturing and Collision-free Constraints”, IEEE Computational Intelligence Magazine, Vol. 7, No. 1, pp.
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371. Arnaud Zinflou, Caroline Gagne and Marc Gravel, “GISMOO: A new hybrid genetic/immune strategy for multipleobjective optimization”, Computers & Operations Research, Vol. 39, No. 9, pp. 1951–1968, September 2012.
372. Khairy Elsayed and Chris Lacor, “Modeling and Pareto optimization of gas cyclone separator performance using RBF
type artificial neural networks and genetic algorithms”, Poweder Technology, Vol. 217, pp. 84–99, February 2012.
373. Yavuz Cengiz and Eray Konar, “Pareto-optimal synthesis of microwave amplifier to design the noise-constrained gain
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374. T. Gomez, M. Hernandez, J. Molina, M.A. Leon, E. Aldana and R. Caballero, “A multiobjective model for forest
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375. C.A. Garcia Montoya and S. Mendoza Toro, “Implementation of an evolutionary algorithm in planning investment in a
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376. Sunith Bandaru and Kalyanmoy Deb, “Towards automating the discovery of certain innovative design principles through
a clustering-based optimization technique”, Engineering Optimization, Vol. 43, No. 9, pp. 911–941, 2011.
377. Shuo Xu, Ze Ji, Duc Truong Pham and Fan Yu, “Binary Bees Algorithm - bioinspiration from the foraging mechanism
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378. Ben G. Small, Barry W. McColl, Richard Allmendinger, J¨
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379. Manojkumar Ramteke and Rajagopalan Srinivasan, “Novel genetic algorithm for short-term scheduling of sequence
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380. Yun-Geun Lee, Bob Mckay, Kang-Il Kim, Dong-Kyun Kim and Nguyen Xuan Hoai, “Investigating vesicular selection A
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381. Guillermo Molina, Francisco Luna, Antonio J. Nebro and Enrique Alba, “An efficient local improvement operator for
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382. W.L. Wang, X.J. Yang, G.X. Xu and Y. Huang, “Multi-objective design optimization of the complete valve system
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383. Jose L. Bernal-Agustin and Rodolfo Dufo-Lopez, “Simulation and optimization of stand-alone hybrid renewable energy
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384. Kwang Mong Sim and Bo An, “Evolving Best-Response Strategies for Market-Driven Agents Using Aggregative Fitness
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385. Md. Rafiul Hassan, Baikunth Nath, Michael Kirley and Joarde Kamruzzaman, “A hybrid of multiobjective Evolutionary
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386. Kent McClymont and Ed Keedwell, “Deductive Sort and Climbing Sort: New Methods for Non-Dominated Sorting”,
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387. Teodor Marcu, Birgit K¨
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388. Christian Gagne and Marc Parizeau, “Coevolution of nearest neighbor classifiers”, International Journal of Pattern
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389. B.Y. Qu and P.N. Suganthan, “Constrained multi-objective optimization algorithm with an ensemble of constraint
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390. Manojkumar Ramteke and Santosh K. Gupta, “Kinetic Modeling and Reactor Simulation and Optimization of Industrially Important Polymerization Processes: a Perspective”, International Journal of Chemical Reactor Engineering, Vol.
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391. Arnaud Liefooghe, Laetitia Jourdan and El-Ghazali Talbi, “A software framework based on a conceptual unified model
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392. Massimiliano Manfren, Paola Caputo and Gaia Costa, “Paradigm shift in urban energy systems through distributed
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393. P.M. Reed and J.B. Kollat, “Save now, pay later? Multi-period many-objective groundwater monitoring design given
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394. C.W. Bong and M. Rajeswari, “Multiobjective clustering with metaheuristic: current trends and methods in image
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396. H. Kordabadi and A. Jahanmiri, “A pseudo-dynamic optimization of a dual-stage methanol synthesis reactor in the face
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397. David Daum and Nicolas Morel, “Assessing the saving potential of blind controller via multi-objective optimization”,
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398. Wei-Mei Chen, Hsien-Kuei Hwang and Tsung-Hsi Tsai, “Maxima-finding algorithms for multidimensional samples: A
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399. Lina Perelman, Avi Ostfeld and Elad Salomons, “Cross Entropy multiobjective optimization for water distribution
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400. Michael A. Trick and Hakan Yildiz, “Locally Optimized Crossover for the Traveling Umpire Problem”, European Journal
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401. Diego P. Pinto-Roa, Benjamin Baran and Carlos A. Brizuela, “Routing and wavelength converter allocation in WDM
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402. Marc Holze and Norbert Ritter, “System models for goal-driven self-management in autonomic databases”, Data &
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403. Karsten Hentsch and Peter K¨
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404. Renata Furtuna, Silvia Curteanu and Carmen Racles, “NSGA-II-RJG applied to multi-objective optimization of polymeric nanoparticles synthesis with silicone surfactants”, Central European Journal of Chemistry, Vol. 9, No. 6, pp.
1080–1095, December 2011.
405. Ronghua Shang, Licheng Jiao, Fang Liu and Wenping Ma, “A Novel Immune Clonal Algorithm for MO Problems”,
IEEE Transactions on Evolutionary Computation, Vol. 16, No. 1, pp. 35–50, February 2012.
406. K.C. Tan, Q. Yu and J.H. Ang, “A dual-objective evolutionary algorithm for rules extraction in data mining”, Computational Optimization and Applications, Vol. 34, No. 2, pp. 273–294, June 2006.
407. J.B. Kollat, P.M. Reed and J.R. Kasprzyk, “A new epsilon-dominance hierarchical Bayesian optimization algorithm for
large multiobjective monitoring network design problems”, Advances in Water Resources, Vol. 31, No. 5, pp. 828–845,
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408. Mohammed Shalaby and Kazuhiro Saitou, “Design for Disassembly With High-Stiffness Heat-Reversible Locator-Snap
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409. B. Descamps, R. Filomeno Coelho, L. Ney and Ph. Bouillard, “Multicriteria optimization of lightweight bridge structures
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410. I-Tung Yang and Jui-Sheng Chou, “Multiobjective optimization for manpower assignment in consulting engineering
firms”, Applied Soft Computing, Vol. 11, No. 1, pp. 1183–1190, January 2011.
411. Hesham Kamel, Ramin Sedaghati and Mamoun Medraj, “Crashworthiness improvement of a pickup truck’s chassis frame
using the Pareto-Front and genetic algorithm”, International Journal of Heavy Vehicle Systems, Vol. 18, No. 1, pp.
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412. Wahabou Abdou, Adrien Henriet, Christelle Bloch, Dominique Dhoutaut, Damien Charlet and Francois Spies, “Using
an evolutionary algorithm to optimize the broadcasting methods in mobile ad hoc networks”, Journal of Network and
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413. Yongtai Huang and Lei Liu, “Multiobjective Water Quality Model Calibration Using a Hybrid Genetic Algorithm and
Neural Network-Based Approach”, Journal of Environmental Engineering–ASCE, Vol. 136, pp. 1020–1031, October
2010.
414. Bruno Urli and Francois Terrien, “Project portfolio selection model, a realistic approach”, International Transactions in
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415. Roger M. Jarvis, William Rowe, Nicola R. Yaffe, Richard O’Connor, Joshua D. Knowles, Ewan W. Blanch and Royston
Goodacre, “Multiobjective evolutionary optimisation for surface-enhanced Raman scattering”, Analytical and Bioanalytical Chemistry, Vol. 397, No. 5, pp. 1893–1901, July 2010.
416. David Daum and Nicolas Morel, “Assessing the total energy impact of manual and optimized blind control in combination
with different lighting schedules in a building simulation environment”, Journal of Building Performance Simulation,
Vol. 3, No. 1, pp. 1–16, 2010.
417. Minqiang Li, Dan Lin and Shouyang Wang, “Solving a type of biobjective bilevel programming problem using NSGAII”,k Computers & Mathematics with Applications, Vol. 59, No. 2, pp. 706–715, January 2010.
418. Zhe Xu and Susan Lu, “Multi-objective optimization of sensor array using genetic algorithm”, Sensors and Actuators
B-Chemical, Vol. 160, No. 1, pp. 278–286, December 15, 2011.
419. Karim Hamza and Kazuhiro Saitou, “A Co-Evolutionary Approach for Design Optimization via Ensembles of Surrogates
With Application to Vehicle Crashworthiness”, Journal of Mechanical Design, Vol. 134, No. 1, Article Number: 011001,
January 2012.
420. K. Rodriguez-Vazquez, M.L. Arganis-Juarez, C. Cruickshank-Villanueva and R. Dominguez-Mora, “Rainfall-runoff modelling using genetic programming”, Journal of Hydroinformatics, Vol. 14, No. 1, pp. 108–121, January 2012.
421. Monica Carvalho, Miguel A. Lozano and Luis M. Serra, “Multicriteria synthesis of trigeneration systems considering
economic and environmental aspects”, Applied Energy, Vol. 91, No. 1, pp. 245–254, March 2012.
422. Peter A. N. Bosman, “On Gradients and Hybrid Evolutionary Algorithms for Real-Valued Multiobjective Optimization”,
423. Rocio L. Cecchini, Ignacio Ponzoni and Jessica A. Carballido, “Multi-objective evolutionary approaches for intelligent
design of sensor networks in the petrochemical industry”, Expert Systems with Applications, Vol. 39, No. 3, pp. 2643–
2649, February 15, 2012.
424. Wenping Zou, Yunlong Zhu, Hanning Chen and Beiwei Zhang, “Solving Multiobjective Optimization Problems Using
Artificial Bee Colony Algorithm”, Discrete Dynamics in Nature and Society, Article Number: 569784, 2011.
425. Eduardo Fernandez Gonzalez, Edy Lopez Cervantes, Jorge Navarro Castillo and Ines Vega Lopez, “Application of MultiObjective Metaheuristics to Public Portfolio Selection Through Multidimensional Modelling of Social Return”, Gestion
y Politica Publica, Vol. 20, No. 2, pp. 381–432, 2011.
426. Shuang Wei and Henry Leung, “A Novel Ranking Method Based on Subjective Probability Theory for Evolutionary
Multiobjective Optimization”, Mathematical Problems in Engineering, Article Number: 695087, 2011.
427. Joaquin Izquierdo, Idel Montalvo, Rafael Perez-Garcia and Agustin Matias, “On the Complexities of the Design of Water
Distribution Networks”, Mathematical Problems in Engineering, Vol. Article Number: 947961, 2012.
428. Karthik Sindhya, Kalyanmoy Deb and Kaisa Miettinen, “Improving convergence of evolutionary multi-objective optimization with local search: a concurrent-hybrid algorithm”, Natural Computing, Vol. 10, No. 4, pp. 1407–1430,
December 2011.
429. Dan Zhang and Zhen Gao, “Hybrid head mechanism of the groundhog-like mine rescue robot”, Robotics and ComputerIntegrated Manufacturing, Vol. 27, No. 2, pp. 460–470, April 2011.
430. Weihong Li, Lijuan Liu and Weiguo Gong, “Multi-objective uniform design as a SVM model selection tool for face
recognition”, Expert Systems with Applications, Vol. 38, No. 6, pp. 6689–6695, June 2011.
431. Gustavo Olague and Leonardo Trujillo, “Evolutionary-computer-assisted design of image operators that detect interest
points using genetic programming”, Image and Vision Computing, Vol. 29, No. 7, pp. 484–498, June 2011.
432. Kejing Li and Xiaobing Zhang, “Multi-Objective Optimization of Interior Ballistic Performance Using NSGA-II”, Propellants Explosives Pyrotechnics, Vol. 36, No. 3, pp. 282–290, June 2011.
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433. Everardo Gutierrez and Carlos Brizuela, “An Enhanced MOGWW for the bi-objective Quadratic Assignment Problem”,
International Journal of Computational Intelligence Systems, Vol. 4, No. 4, pp. 530–549, June-August 2011.
434. Shih-Pin Chen and Ming-Jiun Tsai, “Time-cost trade-off analysis of project networks in fuzzy environments”, European
Journal of Operational Research, Vol. 212, No. 2, pp. 386–397, July 16, 2011.
435. Kishalay Mitra and Sushanta Majumder, “Successive approximate model based multi-objective optimization for an
industrial straight grate iron ore induration process using evolutionary algorithm”, Chemical Engineering Science, Vol.
66, No. 15, pp. 3471–3481, August 1, 2011.
436. E. David Ford and Maureen C. Kennedy, “Assessment of uncertainty in functional-structural plant models”, Annals of
Botany, Vol. 108, No. 6, pp. 1043–1053, October 2011.
437. Antonio L. Marquez, Raul Banos, Consolacion Gil, Maria G. Montoya, Francisco Manzano-Agugliaro and Francisco G.
Montoya, “Multi-objective crop planning using pareto-based evolutionary algorithms”, Agricultural Economics, Vol. 42,
No. 6, pp. 649–656, November 2011.
438. Oscar Daniel Chuk and Benjamin R. Kuchen, “Supervisory control of flotation columns using multi-objective optimization”, Minerals Engineering, Vol. 24, No. 14, pp. 1545–1555, November 2011.
439. H. Komoto, T. Tomiyama, S. Silvester, and H. Brezet, “Analyzing supply chain robustness for OEMs from a life cycle
perspective using life cycle simulation”, International Journal of Production Economics, Vol. 134, No. 2, pp. 447–457,
December 2011.
440. Rajan Filomeno Coelho and Philippe Bouillard, “Multi-Objective Reliability-Based Optimization with Stochastic Metamodels”, Evolutionary Computation, Vol. 19, No. 4, pp. 525–560, Winter 2011.
441. Rafael Alcala, Yusuke Nojima, Francisco Herrera and Hisao Ishibuchi, “Multiobjective genetic fuzzy rule selection of
single granularity-based fuzzy classification rules and its interaction with the lateral tuning of membership functions”,
Soft Computing, Vol. 15, No. 12, pp. 2303–2318, December 2011.
442. Leonardo Trujillo, Gustavo Olague, Evelyne Lutton, Francisco Fernandez de Vega, Leon Dozal and Eddie Clemente,
“Speciation in Behavioral Space for Evolutionary Robotics”, Journal of Intelligent & Robotic Systems, Vol. 64, Nos.
3-4, pp. 323–351, December 2011.
443. Rajeev Kumar and Nilanjan Banerjee, “Multiobjective network topology design”, Applied Soft Computing, Vol. 11, No.
8, pp. 5120–5128, December 2011.
444. Ignacy Kaliszewski, J. Miroforidis and Dmitry Podkopaev, “Interactive Multiple Criteria Decision Making based on preference driven Evolutionary Multiobjective Optimization with controllable accuracy”, European Journal of Operational
Research, Vol. 216, No. 1, pp. 188–199, January 1, 2012.
445. S. Afshin Mansouri, David Gallear and Mohammad H. Askariazad, “Decision support for build-to-order supply chain
management through multiobjective optimization”, International Journal of Production Economics, Vol. 135, No. 1,
pp. 24–36, January 2012.
446. Sultan Noman Qasem and Siti Mariyam Shamsuddin, “Memetic Elitist Pareto Differential Evolution algorithm based
Radial Basis Function Networks for classification problems”, Applied Soft Computing, Vol. 11, No. 8, pp. 5565–5581,
December 2011.
447. Hisao Ishibuchi, Yusuke Nakashima and Yusuke Nojima, “Performance evaluation of evolutionary multiobjective optimization algorithms for multiobjective fuzzy genetics-based machine learning”, Soft Computing, Vol. 15, No. 12, pp.
2415–2434, December 2011.
448. Ke Li, Sam Kwong, Jingjing Cao, Miqing Li, Jinhua Zheng and Ruimin Shen, “Achieving balance between proximity
and diversity in multi-objective evolutionary algorithm”, Information Sciences, Vol. 182, No. 1, pp. 220–242, January
1, 2012.
449. Andre B. de Carvalho and Aurora Pozo, “Measuring the convergence and diversity of CDAS Multi-Objective Particle
Swarm Optimization Algorithms: A study of many-objective problems”, Neurocomputing, Vol. 75, No. 1, pp. 43–51,
January 1, 2012.
450. H. Li and D. Landa-Silva, “An Adaptive Evolutionary Multi-Objective Approach Based on Simulated Annealing”,
Evolutionary Computation, Vol. 19, No. 4, pp. 561–595, Winter 2011.
451. Thomas Tometzki and Sebastian Engell, “Risk conscious solution of planning problems under uncertainty by hybrid
multi-objective evolutionary algorithms”, Computers & Chemical Engineering, Vol. 35, No. 11, pp. 2521–2539, November 15, 2011.
452. Hans-Friedrich K¨
ohn, “A review of multiobjective programming and its application in quantitative psychology”, Journal
of Mathematical Psychology, Vol. 55, No. 5, pp. 386–396, October 2011.
453. Sai Ho Yeung and Kim Fung, “Multiobjective Optimization”, IEEE Microwave Magazine, Vol. 12, No. 6, pp. 120–133,
October 2011.
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454. A. Kaveh and K. Laknejadi, “A novel hybrid charge system search and particle swarm optimization method for multiobjective optimization”, Expert Systems with Applications, Vol. 38, No. 12, pp. 15475–15488, November-December
2011.
455. K.P. Anagnostopoulos and G. Mamanis, “The mean-variance cardinality constrained portfolio optimization problem:
An experimental evaluation of five multiobjective evolutionary algorithms”, Expert Systems with Applications, Vol. 38,
No. 11, pp. 14208–14217, October 2011.
456. Karthik Sindhya, Sauli Ruuska, Tomi Haanp¨
aä and Kaisa Miettinen, “A new hybrid mutation operator for multiobjective
optimization with differential evolution”, Soft Computing, Vol. 15, No. 10, pp. 2041–2055, October 2011.
457. Yi Chen, Yong Ma, Zheng Lu, Lixia Qiu and Jin He, “Terahertz spectroscopic uncertainty analysis for explosive mixture
components determination using multi-objective micro-genetic algorithm”, Advances in Engineering Software, Vol. 42,
No. 9, pp. 649–659, September 2011.
458. Emiliano Carre˜
no Jara, “Long memory time series forecasting by using genetic programming”, Genetic Programming
and Evolvable Machines, Vol. 12, No. 4, pp. 429–456, December 2011.
459. Zbigniew Sekulski, “Multi-objective optimization of high speed vehicle-passenger catamaran by genetic algorithm Part
III Analysis of the results”, Polish Maritime Research, Vol. 18, No. 4, pp. 3–13, 2011.
II Computational simulations”, Polish Maritime Research, Vol. 18, No. 3, pp. 3–30, 2011.
461. Zbigniew Sekulski, “Multi-objective topology and size optimization of high-speed vehicle-passenger catamaran structure
by genetic algorithm”, Marine Structures, Vol. 23, No. 4, pp. 405–433, October 2010.
462. Yong Zhang, Dun-wei Gong and Zhong-hai Ding, “Handling multi-objective optimization problems with a multi-swarm
cooperative particle swarm optimizer”, Expert Systems with Applications, Vol. 38, No. 11, pp. 13933–13941, October
2011.
463. Hisao Ishibuchi, Yuji Sakane, Noritaka Tsukamoto and Yusuke Nojima, “Implementation of cellular genetic algorithms
with two neighborhood structures for single-objective and multi-objective optimization”, Soft Computing, Vol. 15, No.
9, pp. 1749–1767, September 2011.
464. Rodolfo Dufo-Lopez, Jose L. Bernal-Agustin, Jose M. Yusta-Loyo, Jose A. Dominguez-Navarro, Ignacio J. RamirezRosado, Juan Lujano and Ismael Aso, “Multi-objective optimization minimizing cost and life cycle emissions of standalone PV-wind-diesel systems with batteries storage”, Applied Energy, Vol. 88, No. 11, pp. 4033–4041, November
2011.
465. I. Alberto and P.M. Mateo, “A crossover operator that uses Pareto optimality in its definition”, TOP, Vol. 19, No. 1,
pp. 67–92, July 2011.
466. Manuel Chica, Oscar Cordon and Sergio Damas, “An advanced multiobjective genetic algorithm design for the time and
space assembly line balancing problem”, Computers & Industrial Engineering, Vol. 61, No. 1, pp. 103–117, August
2011.
467. David R. White, Andrea Arcuri and John A. Clark, “Evolutionary Improvement of Programs”, IEEE Transactions on
Evolutionary Computation, Vol. 15, No. 4, pp. 515–538, August 2011.
468. Slim Bechikh, Lamjed Ben Said and Khaled Ghédira, “Searching for knee regions of the Pareto front using mobile
reference points”, Soft Computing, Vol. 15, No. 9, pp. 1807–1823, 2011.
469. Alvaro Luis Bustamante, José M. Molina López and Miguel A. Patricio, “MIJ2K Optimization using evolutionary
multiobjective optimization algorithms”, Expert Systems with Applications, Vol. 38, No. 9, pp. 10999–11010, September
2011.
470. Renata Furtuna, Silvia Curteanu and Florin Leon, “An elitist non-dominated sorting genetic algorithm enhanced with a
neural network applied to the multi-objective optimization of a polysiloxane synthesis process”, Engineering Applications
of Artificial Intelligence, Vol. 24, No. 5, pp. 772–785, August 2011.
471. Debanga Nandan Mondal, Kadambini Sarangi, Frank Pettersson, Prodip Kumar Sen, Henrik Saxen and Nirupam
Chakraborti, “Cu-Zn separation by supported liquid membrane analyzed through Multi-objective Genetic Algorithms”,
Hydrometallurgy, Vol. 107, Nos. 3-4, pp. 112–123, May 2011.
472. Oscar Cordon, “A historical review of evolutionary learning methods for Mamdani-type fuzzy rule-based systems: Designing interpretable genetic fuzzy systems”, International Journal of Approximate Reasoning, Vol. 52, No. 6, pp.
894–913, September 2011.
473. H. Moradi, M. Zandieh and Iraj Mahdavi, “Non-dominated ranked genetic algorithm for a multi-objective mixed-model
assembly line sequencing problem”, International Journal of Production Research, Vol. 49, No. 12, pp. 3479–3499, 2011.
474. Wei-Chang Yeh and Mei-Chi Chuang, “Using multi-objective genetic algorithm for partner selection in green supply
chain problems”, Expert Systems with Applications, Vol. 38, No. 4, pp. 4244–4253, April 2011.
475. Reza Ghaemi, Nasir bin Sulaiman, Hamidah Ibrahim and Norwati Mustapha, “A review: accuracy optimization in
clustering ensembles using genetic algorithms”, Artificial Intelligence Review, Vol. 35, No. 4, pp. 287–318, April 2011.
24
476. Shafaq B. Chaudhry, Victor C. Hung, Ratan K. Guha and Kenneth O. Stanley, “Pareto-based evolutionary computational
approach for wireless sensor placement”, Engineering Applications of Artificial Intelligence, Vol. 24, No. 3, pp. 409–425,
April 2011.
477. H. Safikhani, M.A. Akhavan-Behabadi, N. Nariman-Zadeh and M.J. Mahmood Abadi, “Modeling and multi-objective
optimization of square cyclones using CFD and neural networks”, Chemical Engineering Research & Design, Vol. 89,
No. 3A, pp. 301–309, March 2011.
478. M.Sh. Levin and M.V. Petukhov, “Connection of Users with a Telecommunications Network: Multicriteria Assignment
Problem”, Journal of Communications Technology and Electronics, Vol. 55, No. 12, pp. 1532–1541, December 2010.
479. P. Ghobadi, M. Yahyaei and S. Banisi, “Optimization of the performance of flotation circuits using a genetic algorithm
oriented by process-based rules”, International Journal of Mineral Processing, Vol. 98, Nos. 3-4, pp. 174–181, March 9,
2011.
480. Peter Vamplew, Richard Dazeley, Adam Berry, Rustam Issabekov and Evan Dekker, “Empirical evaluation methods for
multiobjective reinforcement learning algorithms”, Machine Learning, Vol. 84, Nos. 1-2, pp. 51–80, July 2011.
481. Luis A. Moncayo-Martinez and David Z. Zhang, “Multi-objective ant colony optimisation: A meta-heuristic approach
to supply chain design”, International Journal of Production Economics, Vol. 131, No. 1, pp. 407–420, May 2011.
482. M.P. Cuellar, S. Capel-Cuevas, M.C. Pegalajar, I. de Orbe-Paya and L.F. Capitan-Vallvey, “Minimization of sensing
elements for full-range optical pH device formulation”, New Journal of Chemistry, Vol. 35, No. 5, pp. 1042–1053, 2011.
483. B. Sankararao and Chang Kyoo Yoo, “Development of a Robust Multiobjective Simulated Annealing Algorithm for
Solving Multiobjective Optimization Problems”, Industrial & Engineering Chemistry Research, Vol. 50, No. 11, pp.
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484. Pankaj Rajak, Ujjal Tewary, Sumitesh Das, Baidurya Bhattacharya and Nirupam Chakraborti, “Phases in Zn-coated
Fe analyzed through an evolutionary meta-model and multi-objective Genetic Algorithms”, Computational Materials
Science, Vol. 50, No. 8, pp. 2502–2516, June 2011.
485. Itishree Mohanty, Debashish Bhattacharjee and Shubhabrata Datta, “Designing cold rolled IF steel sheets with optimized
tensile properties using ANN and GA”, Computational Materials Science, Vol. 50, No. 8, pp. 2331–2337, June 2011.
486. Marianne Boix, Ludovic Montastruc, Luc Pibouleau, Catherine Azzaro-Pantel and Serge Domenech, “A multiobjective
optimization framework for multicontaminant industrial water network design”, Journal of Environmental Management,
Vol. 92, No. 7, pp. 1802–1808, July 2011.
487. Zhanpeng Jin and Allen C. Cheng, “SubsetTrio: An Evolutionary, Geometric, and Statistical Benchmark Subsetting
Framework”, ACM Transactions on Modeling and Computer Simulation, Vol. 21, No. 3, Article Number: 21, March
2011.
488. Chien-Ho Ko and Shu-Fan Wang, “Precast production scheduling using multi-objective genetic algorithms”, Expert
Systems with Applications, Vol. 38, No. 7, pp. 8293–8302, July 2011.
489. Darrell F. Lochtefeld and Frank W. Ciarallo, “Helper-objective optimization strategies for the Job-Shop Scheduling
Problem”, Applied Soft Computing, Vol. 11, No. 6, pp. 4161–4174, September 2011.
490. Markus Hartikainen, Kaisa Miettinen and Margaret M. Wiecek, “Constructing a Pareto front approximation for decision
making”, Mathematical Methods of Operations Research, Vol. 73, No. 2, pp. 209–234, April 2011.
491. Ata Allah Taleizadeh, Farnaz Barzinpour and Hui-Ming Wee, “Meta-heuristic algorithms for solving a fuzzy single-period
problem”, Mathematical and Computer Modelling, Vol. 54, Nos. 5-6, pp. 1273–1285, September 2011.
492. Jiaquan Gao and Jun Wang, “A hybrid quantum-inspired immune algorithm for multiobjective optimization”, Applied
Mathematics and Computation, Vol. 217, No. 9, pp. 4754–4770, January 1, 2011.
493. Y.P. Ju and C.H. Zhang, “Multi-point and multi-objective optimization design method for industrial axial compressor
cascades”, Proceedings of the Institution of Mechanical Engineers Part C–Journal of Mechanical Engineering Science,
Vol. 225, No. C6, pp. 1481–1493, 2011.
494. A. Kundu and P.K. Dan, “The Scope of Genetic Algorithms in Dealing with Facility Layout Problems”, South African
Journal of Industrial Engineering, Vol. 21, No. 2, pp. 39–49, November 2010.
495. Ernesto Benini, Rita Ponza and Andrea Massaro, “High-Lift Multi-Element Airfoil Shape and Setting Optimization
Using Multi-Objective Evolutionary Algorithms”, Journal of Aircraft, Vol. 48, No. 2, pp. 683–696, March-April 2011.
496. Kishalay Mitra, “Handling Uncertainty in Kinetic Parameters in Optimal Operation of a Polymerization Reactor”,
Materials and Manufacturing Processes, Vol. 26, No. 3, pp. 446–454, 2011.
497. Yu Wang, Bin Li and Yunbi Chen, “Digital IIR filter design using multi-objective optimization evolutionary algorithm”,
Applied Soft Computing, Vol. 11, No. 2, pp. 1851–1857, March 2011.
498. Yi Sun, Chaoyong Zhang, Liang Gao and Xiaojuan Wang, “Multi-objective optimization algorithms for flow shop
scheduling problem: a review and prospects”, International Journal of Advanced Manufacturing Technology, Vol. 55,
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25
499. Ali R. Yildiz and Kazuhiro Saitou, “Topology Synthesis of Multicomponent Structural Assemblies in Continuum Domains”, Journal of Mechanical Design, Vol. 133, No. 1, Article Number: 011008, January 2011.
500. Yu Liang, XiaoQuan Cheng, ZhengNeng Li and JinWu Xiang, “Multi-objective robust airfoil optimization based on
non-uniform rational B-spline (NURBS) representation”, Science China-Technological Sciences, Vol. 53, No. 10, pp.
2708–2717, October, 2010.
501. Satoshi Kitayama, Masao Arakawa and Koetsu Yamazaki, “Differential evolution as the global optimization technique
and its application to structural optimization”, Applied Soft Computing, Vol. 11, No. 4, pp. 3792–3803, June 2011.
502. R.P. Dionisio, G. Parca, C. Reis and A.L. Teixeira, “Operational parameter optimisation of MZI-SOA using multiobjective genetic algorithms”, Electronics Letters, Vol. 47, No. 9, pp. 561–562, April 28, 2011.
503. Gustavo C.M. Ferreira, S.P.N. Cani, M.J. Pontes and M.E.V. Segatto, “Optimization of Distributed Raman Amplifiers
Using a Hybrid Genetic Algorithm With Geometric Compensation Technique”, IEEE Photonics Journal, Vol. 3, No. 3,
pp. 390–399, June 2011.
504. P. Rocca, G. Oliveri and A. Massa, “Differential Evolution as Applied to Electromagnetics”, IEEE Antennas and
Propagation Magazine, Vol. 53, No. 1, pp. 38–49, February 2011.
505. Yu Liang, Xiao-quan Cheng, Zheng-neng Li and Jin-wu Xiang, “Robust Multi-Objective Wing Design Optimization via
CFD Approximation Model”, Engineering Applications of Computational Fluid Mechanics, Vol. 5, No. 2, pp. 286–300,
June 2011.
506. Yann Cooren, Maurice Clerc and Patrick Siarry, “MO-TRIBES, an adaptive multiobjective particle swarm optimization
algorithm”, Computational Optimization and Applications, Vol. 49, No. 2, pp. 379–400, June 2011.
507. Miltiadis Kotinis, “Implementing co-evolution and parallelization in a multi-objective particle swarm optimizer”, Engineering Optimization, Vol. 43, No. 6, pp. 635–656, June 2011.
508. Karthik Sindhya and Kaisa Miettinen, “New Perspective to Continuous Casting of Steel with a Hybrid Evolutionary
Multiobjective Algorithm”, Materials and Manufacturing Processes, Vol. 26, No. 3, pp. 481–492, 2011.
509. Rajan Filomeno Coelho, Jeremy Lebon and Philippe Bouillard, “Hierarchical stochastic metamodels based on moving
least squares and polynomial chaos expansion”, Structural and Multidisciplinary Optimization, Vol. 43, No. 5, pp.
707–729, May 2011.
510. Debarati Kundu, Kaushik Suresh, Sayan Ghosh, Swagatam Das, B.K. Panigrahi and Sanjoy Das, “Multi-objective
optimization with artificial weed colonies”, Information Sciences, Vol. 181, No. 12, pp. 2441–2454, June 15, 2011.
511. Chin-Wei Bong and Mandava Rajeswari, “Multi-objective nature-inspired clustering and classification techniques for
image segmentation”, Applied Soft Computing, Vol. 11, No. 4, pp. 3271–3282, June 2011.
512. A. Castelletti, A.V. Lotov and R. Soncini-Sessa, “Visualization-based multi-objective improvement of environmental
decision-making using linearization of response surfaces”, Environmental Modelling & Software, Vol. 25, No. 12, pp.
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513. Ruchit Shah and Patrick Reed, “Comparative analysis of multiobjective evolutionary algorithms for random and correlated instances of multiobjective d-dimensional knapsack problems”, European Journal of Operational Research, Vol.
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514. Salem F. Adra and Peter J. Fleming, “Diversity Management in Evolutionary Many-Objective Optimization”, IEEE
Transactions on Evolutionary Computation, Vol. 15, No. 2, pp. 183–195, April 2011.
515. Burcin Cakir, Fulya Altiparmak and Berna Dengiz, “Multi-objective optimization of a stochastic assembly line balancing:
A hybrid simulated annealing algorithm”, Computers & Industrial Engineering, Vol. 60, No. 3, pp. 376–384, April 2011.
516. Renan Cabrera, Ofer M. Shir, Rebing Wu and Herschel Rabitz, “Fidelity between unitary operators and the generation
of robust gates against off-resonance perturbations”, Journal of Physics A–Mathematical and Theoretical, Vol. 44, No.
9, Article Number 095302, March 4, 2011.
517. Nadia Nedjah, Marcus Vinicius Carvalho da Silva and Luiza de Macedo Mourelle, “Customized computer-aided application mapping on NoC infrastructure using multi-objective optimization”, Journal of Systems Architecture, Vol. 57, No.
1, pp. 79–94, January 2011.
518. James Bekker and Chris Aldrich, “The cross-entropy method in multi-objective optimisation: An assessment”, European
Journal of Operational Research, Vol. 211, No. 1, pp. 112–121, May 16, 2011.
519. Fatimah Sham Ismail, Rubiyah Yusof and Marzuki Khalid, “Self Organizing Multi-Objective Optimization Problem”,
International Journal of Innovative Computing Information and Control, Vol. 7, No. 1, pp. 301–314, January 2011.
520. Zhong-Zhong Jiang, W.H. Ip, H.C.W. Lau and Zhi-Ping Fan, “Multi-objective optimization matching for one-shot
multi-attribute exchanges with quantity discounts in E-brokerage”, Expert Systems with Applications, Vol. 38, No. 4,
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521. K. Sivakumar, C. Balamurugan and S. Ramabalan, “Simultaneous optimal selection of design and manufacturing tolerances with alternative manufacturing process selection”, Computer-Aided Design, Vol. 43, No. 2, pp. 207–218, February
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26
522. Prithwish Chakraborty, Swagatam Das, Gourab Ghosh Roy and Ajith Abraham, “On convergence of the multi-objective
particle swarm optimizers”, Information Sciences, Vol. 181, No. 8, pp. 1411–1425, April 15, 2011.
523. K. Sivakumar, C. Balamurugan and S. Ramabalan, “Concurrent multi-objective tolerance allocation of mechanical
assemblies considering alternative manufacturing process selection”, International Journal of Advanced Manufacturing
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524. Magdalene Marinaki, Yannis Marinakis and Georgios E. Stavroulakis, “Fuzzy control optimized by a Multi-Objective
Particle Swarm Optimization algorithm for vibration suppression of smart structures”, Structural and Multidisciplinary
Optimization, Vol. 43, No. 1, pp. 29–42, January 2011.
525. Juan C. Vidal, Manuel Mucientes, Alberto Bugar´ın and Manuel Lama, “Machine scheduling in custom furniture industry
through neuro-evolutionary hybridization”, Applied Soft Computing, Vol. 11, No. 2, pp. 1600–1613, March 2011.
526. Mohammad Hamdan, “A dynamic polynomial mutation for evolutionary multi-objective optimization algorithms”, International Journal on Artificial Intelligence Tools, Vol. 20, No. 1, pp. 209–219, February 2011.
527. Kousik Deb and Anirban Dhar, “Optimum design of stone column-improved soft soil using multiobjective optimization
technique”, Computers and Geotechnics, Vol. 38, No. 1, pp. 50–57, January 2011.
528. Carlos R. Garcia-Alonso, Luis Salvador-Carulla, Miguel A. Negrin-Hernandez and Berta Moreno-Kustner, “Development
of a new spatial analysis tool in mental health: Identification of highly autocorrelated areas (hot-spots) of schizophrenia
using a Multiobjective Evolutionary Algorithm model (MOEA/HS)”, Epidemiologia E Psichiatria Sociale–An International Journal for Epidemiology and Psychiatric Sciences, Vol. 19, No. 4, pp. 302–313, October-December 2010.
529. Tsung-Che Chiang, Hsueh-Chien Cheng and Li-Chen Fu, “NNMA: An effective memetic algorithm for solving multiobjective permutation flow shop scheduling problems”, Expert Systems with Applications, Vol. 38, No. 5, pp. 5986–5999,
May 2011.
530. J.B. Kollat, P.M. Reed and R.M. Maxwell, “Many-objective groundwater monitoring network design using bias-aware
ensemble Kalman filtering, evolutionary optimization, and visual analytics”, Water Resources Research, Vol. 47, Article
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531. Lei Gao and Atakelty Hailu, “Comprehensive Learning Particle Swarm Optimizer for Constrained Mixed-Variable Optimization Problems”, International Journal of Computational Intelligence Systems, Vol. 3, No. 6, pp. 832–842, December
2010.
532. Minqiang Li, Liu Liu and Dan Lin, “A fast steady-state epsilon-dominance multi-objective evolutionary algorithm”,
Computational Optimization and Applications, Vol. 48, No. 1, pp. 109–138, January 2011.
533. Nguyen Binh Ta Duong, Suiping Zhou, Wentong Cai, Xueyan Tang and Rassul Ayani, “Multi-objective zone mapping
in large-scale distributed virtual environments”, Journal of Network and Computer Applications, Vol. 34, No. 2, pp.
551–561, March 2011.
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753. A. I. Olcer, “A hybrid approach for multi-objective combinatorial optimisation problems in ship design and shipping”,
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763. J. Sanchis, M. Martinez and X. Blasco, “Multi-objective engineering design using preferences”, Engineering Optimization,
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764. Paulo Fazendeiro, Jose Valente de Oliveira and Witold Pedrycz, “A multiobjective design of a patient and anaesthetistfriendly neuromuscular blockade controller”, IEEE Transactions on Biomedical Engineering, Vol. 54, No. 9, pp. 1667–
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765. Zbigniew Michalewicz and Matthew Michalewicz, “Machine intelligence, adaptive business intelligence, and natural
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777. Marco A. Panduro, Carlos A. Brizuela and David H. Covarrubias, “Design of electronically steerable linear arrays with
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778. Kay-Soon Low and Tze-Shyan Wong, “A multiobjective genetic algorithm for optimizing the performance of hard disk
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782. Sarbajit Pal, Pankaj Ganguly and P.K. Biswas, “Cubic Bezier approximation of a digitized curve”, Pattern Recognition,
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797. Kaisa Miettinen, “Using Interactive Multiobjective Optimization in Continuous Casting of Steel”, Materials and Manufacturing Processes, Vol. 22, No. 5, pp. 585–593, 2007.
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812. J.B. Kollat and P.M. Reed, “A computational scaling analysis of multiobjective evolutionary algorithms in long-term
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822. Julia Handl, Douglas B. Kell and Joshua Knowles, “Multiobjective optimization in bioinformatics and computational
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843. A. Singh and H.H. Lou, “Hierarchical Pareto optimization for the sustainable development of industrial ecosystems”,
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852. Lyndon While, Phil Hingston, Luigi Barone, and Simon Huband, “A Faster Algorithm for Calculating Hypervolume”,
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855. J.J. Huang, G.H. Tzeng and C.S. Ong, “Optimal fuzzy multi-criteria expansion of competence sets using multi-objectives
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856. Z.V.P. Murthy and J.C. Vengal, “Optimization of a reverse osmosis system using genetic algorithm”, Separation Science
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857. Joshua Knowles, “ParEGO: A Hybrid Algorithm With On-Line Landscape Approximation for Expensive Multiobjective
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859. K.B. Matthews, K. Buchan, A.R. Sibbald and S. Craw, “Combining deliberative and computer-based methods for
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860. F. de Toro, E. Ros, S. Mota and J. Ortega, “Evolutionary algorithms for multiobjective and multimodal optimization
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863. M.A. Panduro, C.A. Brizuela, D. Covarrubias and C. Lopez, “A trade-off curve computation for linear antenna arrays
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864. M. Liu, S.A. Burns and Y.K. Wen, “Genetic algorithm based construction-conscious minimum weight design of seismic
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Using the Biogenetic Law of Embryology for Intelligent Optimization”, Industrial & Engineering Chemistry Research,
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1001. Jessica A. Carballido, Ignacio Ponzoni and Nelida B. Brignole, “SID-GA: An evolutionary approach for improving
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1002. X. B. Lam, Y.S. Kim, A.D. Hoang and C.W. Park, “Coupled Aerostructural Design Optimization Using the Kriging
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1003. Robert D. Clark and Edmond Abrahamian, “Using a staged multi-objective optimization approach to find selective
pharmacophore models”, Journal of Computer-Aided Molecular Design, Vol. 23, No. 11, pp. 765–771, November 2009.
1004. G. Nildem Demir, A. Sima Uyar and Sule Gunduz-Oguducu, “Multiobjective evolutionary clustering of Web user sessions:
a case study in Web page recommendation”, Soft Computing, Vol. 14, No. 6, pp. 579–597, April 2010.
1005. K.H. Gudmundsson, F. Jonsdottir and F. Thorsteinsson, “A geometrical optimization of a magneto-rheological rotary
brake in a prosthetic knee”, Smart Materials & Structures, Vol. 19, No. 3, Article Number: 035023, March 2010.
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1008. Manojkumar Ramteke and Santosh K. Gupta, “Biomimicking Altruistic Behavior of Honey Bees in Multi-objective
Genetic Algorithm”, Industrial & Engineering Chemistry Research, Vol. 48, No. 21, pp. 9671–9685, November 4, 2009.
1009. Ujjwal Maulik, Anirban Mukhopadhyay and Sanghamitra Bandyopadhyay, “Finding Multiple Coherent Biclusters in
Microarray Data Using Variable String Length Multiobjective Genetic Algorithm”, IEEE Transactions on Information
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1010. M.H. Kobayashi, H-T. C. Pedro, R.M. Kolonay and G.W. Reich, “On a cellular division method for aircraft structural
design”, Aeronautical Journal, Vol. 113, No. 1150, pp. 821–831, December 2009.
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1011. David Daum and Nicolas Morel, “Identifying important state variables for a blind controller”, Building and Environment,
Vol. 45, No. 4, pp. 887–900, April 2010.
1012. Chung Min Kwan and C.S. Chang, “Timetable synchronization of mass rapid transit system using multiobjective evolutionary approach”, IEEE Transactions on Systems, Man, and Cybernetics Part C–Applications and Reviews, Vol. 38,
No. 5, pp. 636–648, September 2008.
1013. S. Ganguly, S. Datta, P.P. Chattopadhyay and N. Chakraborti, “Designing the Multiphase Microstructure of Steel for
Optimal TRIP Effect: A Multiobjective Genetic Algorithm Based Approach”, Materials and Manufacturing Processes,
Vol. 24, No. 1, pp. 31–37, 2009.
1014. Arijit Biswas, N. Chakraborti and P.K. Sen, “Multiobjective Optimization of Manganese Recovery from Sea Nodules
Using Genetic Algorithms”, Materials and Manufacturing Processes, Vol. 24, No. 1, pp. 22–30, 2009.
1015. Nicolas Jozefowiez, Frederic Semet and El-Ghazali Talbi, “An evolutionary algorithm for the vehicle routing problem
with route balancing”, European Journal of Operational Research, Vol. 195, No. 3, pp. 761–769, June 16, 2009.
1016. Lino J. Alvarez-Vazquez, Eva Balsa-Canto and Aurea Martinez, “Optimal design and operation of a wastewater purification system”, Mathematics and Computers in Simulation, Vol. 79, No. 3, pp. 668–682, December 1, 2008.
1017. A. Rama Mohan Rao and P.P. Shyju, “A Meta-Heuristic Algorithm for Multi-Objective Optimal Design of Hybrid
Laminate Composite Structures”, Computer-Aided Civil and Infrastructure Engineering, Vol. 25, No. 3, pp. 149–170,
April 2010.
¨ gu
1018. G. Nildem Demir, A. S
¸ ima Uyar and S
¸ ule G¨
und¨
uz-Oˇ
¨d¨
uc¨
u, “Multiobjective evolutionary clustering of Web user sessions:
a case study in Web page recommendation”, Soft Computing - A Fusion of Foundations, Methodologies and Applications,
Vol. 14, No. 6, pp. 579–597, January, 2010.
1019. Kaushik Suresh, Debarati Kundu, Sayan Ghosh, Swagatam Das and Ajith Abraham, “Data Clustering Using Multiobjective Differential Evolution Algorithms”, Fundamenta Informaticae, Vol. 97, No. 4, pp. 381–403, 2009.
1020. Kaushik Suresh, Debarati Kundu, Sayan Ghosh, Swagatam Das, Ajith Abraham and Sang Yong Han, “Multi-Objective
Differential Evolution for Automatic Clustering with Application to Micro-Array Data Analysis”, Sensors, Vol. 9, No.
5, pp. 3981–4004, May 2009.
1021. Silvia Curteanu and Maria Cazacu, “Optimization of a Polysiloxane Synthesis Process using Artificial Intelligence Methods”, Revue Roumaine de Chimie, Vol. 53, No. 12, pp. 1141–1148, December 2008.
1022. Zhanpeng Jin and Allen C. Cheng, “Evolutionary Benchmark Subsetting”, IEEE Micro, Vol. 28, No. 6, pp. 20–36,
November-December 2008.
1023. Zhen Gao, Dan Zhang and Yunjian Ge, “Design optimization of a spatial six degree-of-freedom parallel manipulator
based on artificial intelligence approaches”, Robotics and Computer-Integrated Manufacturing, Vol. 26, No. 2, pp.
180–189, April 2010.
1024. Luis Gerardo de la Fraga and Oliver Schutze, “Direct Calibration by Fitting of Cuboids to a Single Image Using
Differential Evolution”, International Journal of Computer Vision, Vol. 81, No. 2, pp. 119–127, February 2009.
1025. Chris Thachuk, Jose Crossa, Jorge Franco, Susanne Dreisigacker, Marilyn Warburton and Guy F. Davenport, “Core
Hunter: an algorithm for sampling genetic resources based on multiple genetic measures”, BMC Bioinformatics, Vol.
10, Article Number 243, August 6, 2009.
1026. Babak Forouraghi, “Optimal tolerance allocation using a multiobjective particle swarm optimizer”, International Journal
of Advanced Manufacturing Technology, Vol. 44, Nos. 7–8, pp. 710–724, October 2009.
1027. Yusuke Nojima, Hisao Ishibuchi and Isao Kuwajima, “Parallel distributed genetic fuzzy rule selection”, Soft Computing,
Vol. 13, No. 5, pp. 511–519, March 2009.
1028. A.F. Carazo, Trinidad Gomez, Julian Molina, Alfredo G. Hernandez-Diaz, Flor M. Guerrero and Rafael Caballero,
“Solving a comprehensive model for multiobjective project portfolio selection”, Computers & Operations Research, Vol.
37, No. 4, pp. 630–639, April 2010.
1029. Eduardo Fernandez, Jorge Navarro and Sergio Bernal, “Handling multicriteria preferences in cluster analysis”, European
1030. Leila Dridi, Alain Mailhot, Marc Parizeau and Jean-Pierre Villeneuve, “Multiobjective Approach for Pipe Replacement
Based on Bayesian Inference of Break Model Parameters”, Journal of Water Resources Planning and Management–
ASCE, Vol. 135, No. 5, pp. 344–354, September-October 2009.
1031. Francisco Martinez-Lopez and Jorge Casillas, “Marketing Intelligent Systems for consumer behaviour modelling by a
descriptive induction approach based on Genetic Fuzzy Systems”, Industrial Marketing Management, Vol. 38, No. 7,
pp. 714–731, October 2009.
1032. David Greiner, Juan J. Aznarez, Orlando Maeso and Gabriel Winter, “Single- and multi-objective shape design of Ynoise barriers using evolutionary computation and boundary elements”, Advances in Engineering Software, Vol. 41, No.
2, pp. 368–378, February 2010.
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1033. Axel Soto, Rocio L. Cecchini, Gustavo E. Vazquez and Ignacio Ponzoni, “Multi-Objective Feature Selection in QSAR
Using a Machine Learning Approach”, QSAR & Combinatorial Science, Vol. 28, Nos. 11–12, pp. 1509–1523, December
2009.
1034. Kishalay Mitra, “Multiobjective optimization of an industrial grinding operation under uncertainty”, Chemical Engineering Science, Vol. 64, No. 23, pp. 5043–5056, December 1, 2009.
1035. J.E. Mendoza, L.A. Villaleiva, M.A. Castro and E.A. Lopez, “Multi-objective Evolutionary Algorithms for DecisionMaking in Reconfiguration Problems Applied to the Electric Distribution Networks”, Studies in Informatics and Control,
1036. A. Liefooghe, L. Jourdan and E.-G. Talbi, “Metaheuristics and cooperative approaches for the Bi-objective Ring Star
Problem”, Computers & Operations Research, Vol. 37, No. 6, pp. 1033–1044, June 2010.
1037. Jeffrey S. Parker and George H. Born, “Direct Lunar Halo Orbit Transfers”, Journal of the Astronautical Sciences, Vol.
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1038. K.P. Anagnostopoulos and G. Mamanis, “A portfolio optimization model with three objectives and discrete variables”,
Computers & Operations Research, Vol. 37, No. 7, pp. 1285–1297, July 2010.
1039. Nicola Beume, “S-Metric Calculation by Considering Dominated Hypervolume as Klee’s Measure Problem”, Evolutionary
Computation, Vol. 17, No. 4, pp. 477–492, Winter 2009.
1040. J.R. Kasprzyk, P.M. Reed, B.R. Kirsch and G.W. Characklis, “Managing population and drought risks using manyobjective water portfolio planning under uncertainty”, Water Resources Research, Vol. 45, Article Number: W12401,
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1041. M.H. Khoshgoftar Manesh and Majid Amidpour, “Multi-objective thermoeconomic optimization of coupling MSF desalination with PWR nuclear power plant through evolutionary algorithms”, Desalination, Vol. 249, No. 3, pp. 1332–1344,
December 25, 2009.
1042. Jacek Zak, Andrzej Jaszkiewicz and Adam Redmer, “Multiple Criteria Optimization Method for the Vehicle Assignment
Problem in a Bus Transportation Company”, Journal of Advanced Transportation, Vol. 43, No. 2, pp. 203–243, 2009.
1043. J.A. Covas and A. Gaspar-Cunha, “Extrusion Scale-up: An Optimization-based Methodology”, International Polymer
Processing, Vol. 24, No. 1, pp. 67–82, March 2009.
1044. Arijit Biswas, N. Chakraborti and P.K. Sen, “A Genetic Algorithms Based Multi-Objective Optimization Approach
Applied to a Hydrometallurgical Circuit for Ocean Nodules”, Mineral Processing and Extractive Metallurgy Review, Vol.
30, No. 2, pp. 163–189, 2009.
1045. A.M. Mora, J.J. Merelo, J.L.J. Laredo, C. Millan and J. Torrecillas, “CHAC, A MOACO Algorithm for Computation of
Bi-Criteria Military Unit Path in the Battlefield: Presentation and First Results”, International Journal of Intelligent
Systems, Vol. 24, No. 7, pp. 818–843, July 2009.
1046. A. Jamali, A. Hajiloo and N. Nariman-zadeh, “Reliability-based robust Pareto design of linear state feedback controllers
using a multi-objective uniform-diversity genetic algorithm (MUGA)”, Expert Systems with Applications, Vol. 37, No.
1, pp. 401–413, January 2010.
1047. Hamidreza Eskandari and Christopher D. Geiger, “Evolutionary multiobjective optimization in noisy problem environments”, Journal of Heuristics, Vol. 15, No. 6, pp. 559–595, December 2009.
1048. Jawed Iqbal and Chandan Guria, “Optimization of an operating domestic wastewater treatment plant using elitist nondominated sorting genetic algorithm”, Chemical Engineering Research & Design, Vol. 87, No. 11A, pp. 1481–1496,
November 2009.
1049. Juliane Muller, “Approximative solutions to the bicriterion Vehicle Routing Problem with Time Windows”, European
Journal of Operational Research, Vol. 202, No. 1, pp. 223–231, April 1, 2010.
1050. Kostas Florios, George Mavrotas and Danae Diakoulaki, “Solving multiobjective, multiconstraint knapsack problems
using mathematical programming and evolutionary algorithms”, European Journal of Operational Research, Vol. 203,
No. 1, pp. 14–21, May 16, 2010.
1051. Anirban Dhar and Bithin Datta, “Saltwater Intrusion Management of Coastal Aquifers. I: Linked Simulation-Optimization”,
Journal of Hydrologic Engineering, Vol. 14, No. 12, pp. 1263–1272, December 2009.
1052. Nicola Beume, Boris Naujoks and Guenter Rudolph, “SMS-EMOA - Effective Evolutionary Multiobjective Optimization”, AT-Automatisierungstechnik, Vol. 56, No. 7, pp. 357–364, 2008.
1053. M. Pouraghaie, K. Atashkari, S.M. Besarati and N. Nariman-Zadeh, “Thermodynamic performance optimization of a
combined power/cooling cycle”, Energy Conversion and Management, Vol. 51, No. 1, pp. 204–211, January 2010.
1054. Anthony Chen, Juyoung Kim, Seungjae Lee and Youngchan Kim, “Stochastic multi-objective models for network design
problem”, Expert Systems with Applications, Vol. 37, No. 2, pp. 1608–1619, March 2010.
1055. Ioannis C. Kampolis and Kyriakos C. Giannakoglou, “Distributed evolutionary algorithms with hierarchical evaluation”,
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1056. Patrick M. Reed, Joshua B. Kollat, Matthew P. Ferringer and Timothy G. Thompson, “Parallel Evolutionary MultiObjective Optimization on Large, Heterogeneous Clusters: An Applications Perspective”, Journal of Aerospace Computing Information and Communication, Vol. 5, No. 11, pp. 460–478, 2008.
1057. N. Chakraborti, S. Moitra, A. Mitra and A. Mukhopadhyay, “Evolutionary and genetic algorithms applied to hot rolling:
A multi-objective rolling schedule studied using particle swarm algorithm”, Transactions of the Indian Institute of Metals,
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1058. Yujia Wang and Yupu Yang, “Particle swarm optimization with preference order ranking for multi-objective optimization”, Information Sciences, Vol. 179, No. 12, pp. 1944–1959, May 30, 2009.
1059. Yujia Wang and Yupu Yang, “Particle swarm with equilibrium strategy of selection for multi-objective optimization”,
European Journal of Operational Research, Vol. 200, No. 1, pp. 187–197, January 1, 2010.
1060. Baidurya Bhattacharya, G.R. Dinesh Kumar, Akash Agarwal, Sakir Erkoc, Arunima Singh and Nirupam Chakraborti,
“Analyzing Fe-Zn system using molecular dynamics, evolutionary neural nets and multi-objective genetic algorithms”,
Computational Materials Science, Vol. 46, No. 4, pp. 821–827, October 2009.
1061. Aimin Zhou, Qingfu Zhang and Yaochu Jin, “Approximating the Set of Pareto-Optimal Solutions in Both the Decision
and Objective Spaces by an Estimation of Distribution Algorithm”, IEEE Transactions on Evolutionary Computation,
Vol. 13, No. 5, pp. 1167–1189, October 2009.
1062. Gisele L. Pappa and Alex A. Freitas, “Evolving rule induction algorithms with multi-objective grammar-based genetic
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1063. Nicola Beume, Carlos M. Fonseca, Manuel Lopez-Ibanez, Luis Paquete and Jan Vahrenhold, “On the Complexity of
Computing the Hypervolume Indicator”, IEEE Transactions on Evolutionary Computation, Vol. 13, No. 5, pp. 1075–
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1064. Anthony Finkelstein, Mark Harman, S. Afshin Mansouri, Jian Ren, Yuanyuan Zhang, “A search based approach to fairness analysis in requirement assignments to aid negotiation, mediation and decision making”, Requirements Engineering,
1065. A. Rama Mohan Rao and K. Lakshmi, “Multi-objective Optimal Design of Hybrid Laminate Composite Structures Using
Scatter Search”, Journal of Composite Materials, Vol. 43, No. 20, pp. 2157–2182, September 2009.
1066. Mario Camara, Julio Ortega and Francisco de Toro, “A single front genetic algorithm for parallel multi-objective optimization in dynamic environments”, Neurocomputing, Vol. 72, Nos. 16–18, pp. 3570–3579, October 2009.
1067. Parames Chutima and Penpak Pinkoompee, “Multi-objective sequencing problems of mixed-model assembly systems
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1068. Lam T. Bui, Hussein A. Abbass and Daryl Essam, “Localization for Solving Noisy Multi-Objective Optimization Problems”, Evolutionary Computation, Vol. 17, No. 3, pp. 379–409, Fall 2009.
Vol. 13, No. 5, pp. 1167–1189, October 2009.
1070. Nicola Beume, Carlos M. Fonseca, Manuel Lopez-Ibanez, Luis Paquete and Jan Vahrenhold, “On the Complexity of
Computing the Hypervolume Indicator”, IEEE Transactions on Evolutionary Computation, Vol. 13, No. 5, pp. 1075–
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1071. Jiaquan Gao and Jun Wang, “WBMOAIS: A novel artificial immune system for multiobjective optimization”, Computers
& Operations Research, Vol. 37, No. 1, pp. 50–61, January 2010.
1072. Rafael Alcala, Pietro Ducange, Francisco Herrera, Beatrice Lazzerini and Francesco Marcelloni, “A Multiobjective
Evolutionary Approach to Concurrently Learn Rule and Data Bases of Linguistic Fuzzy-Rule-Based Systems”, IEEE
Transactions on Fuzzy Systems, Vol. 17, No. 5, pp. 1106–1122, October 2009.
1073. Anthony Chen, Kitti Subprasom and Zhaowang Ji, “A simulation-based multi-objective genetic algorithm (SMOGA)
procedure for BOT network design problem”, Optimization and Engineering, Vol. 7, No. 3, pp. 225–247, September
2006.
1074. Yang Zhang and Peter Rockett, “A Comparison of three evolutionary strategies for multiobjective genetic programming”,
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1075. Manojkumar Ramteke and Santosh K. Gupta, “Multiobjective Optimization of an Industrial Nylon-6 Semi Batch Reactor
Using the a-Jumping Gene Adaptations of Genetic Algorithm and Simulated Annealing”, Polymer Engineering and
Science, Vol. 48, No. 11, pp. 2198–2215, November 2008.
1076. Andrzej Jaszkiewicz and Piotr Zielniewicz, “Pareto memetic algorithm with path relinking for bi-objective traveling
salesperson problem”, European Journal of Operational Research, Vol. 193, No. 3, pp. 885–890, March 16, 2009.
1077. Jose L. Ceciliano Meza, Mehmet Bayram Yildirim and Abu S.M. Masud, “A Multiobjective Evolutionary Programming
Algorithm and Its Applications to Power Generation Expansion Planning”, IEEE Transactions on Systems, Man, and
Cybernetics, Part A–Systems and Humans, Vol. 39, No. 5, pp. 1086–1096, September 2009.
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1078. Hai-Lin Liu, Yuping Wang and Yiu-Ming Cheung, “A Multi-Objective Evolutionary Algorithm using Min-Max Strategy
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1079. Hussein A. Abbass, Sameer Alam and Axel Bender, “MEBRA: Multiobjective Evolutionary-Based Risk Assessment”,
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1080. K.F. Doerner, W.J. Gutjahr, R.F. Hartl, C. Strauss and C. Stummer, “Nature-inspired metaheuristics for multiobjective
activity crashing”, Omega–International Journal of Management Science, Vol. 36, No. 6, pp. 1019–1037, December
2008.
1081. Petra Kersting and Andreas Zabel, “Optimizing NC-tool paths for simultaneous five-axis milling based on multipopulation multi-objective evolutionary algorithms”, Advances in Engineering Software, Vol. 40, No. 6, pp. 452–463,
June 2009.
1082. A. Jamali, N. Nariman-zadeh, A. Darvizeh, A. Masoumi and S. Hamrang, “Multi-objective evolutionary optimization
of polynomial neural networks for modelling and prediction of explosive cutting process”, Engineering Applications of
Artificial Intelligence, Vol. 22, Nos. 4-5, pp. 676–687, June 2009.
1083. Vijay Pratap Singh, Bertrand Duquet, Michel Leger and Marc Schoenauer, “Automatic wave-equation migration velocity
inversion using multiobjective evolutionary algorithms”, Geophysics, Vol. 73, No. 5, pp. 61–73, September-October 2008.
1084. Jose L. Bernal-Agustin and Rodolfo Dufo-Lopez, “Multi-objective design and control of hybrid systems minimizing costs
and unmet load”, Electric Power Systems Research, Vol. 79, No. 1, pp. 170–180, January 2009.
1085. Christos Baloukas, Jose L. Risco-Martin, David Atienza, Christophe Poucet, Lazaros Papadopoulos, Stylianos Mamagkakis, Dimitrios Soudris, J. Ignacio Hidalgo, Francky Catthoor and Juan Lanchares, “Optimization methodology
of dynamic data structures based on genetic algorithms for multimedia embedded systems”, Journal of Systems and
Software, Vol. 82, No. 4, pp. 590–602, April 2009.
1086. Wei Wei, Yixiong Feng, Jianrong Tan and Zhongkai Li, “Product platform two-stage quality optimization design based
on multiobjective genetic algorithm”, Computers & Mathematics with Applications, Vol. 57, Nos. 11–12, pp. 1929–1937,
June 2009.
1087. Leila Dridi, Marc Parizeau, Alain Mailhot and Jean-Pierre Villeneuve, “Using evolutionary optimization techniques for
scheduling water pipe renewal considering a short planning horizon”, Computer-Aided Civil and Infrastructure Engineering, Vol. 23, No. 8, pp. 625–635, November 2008.
1088. David L. Overbye, “The Influence of Darwin on Evolutionary Algorithms from ”Dinner with Darwin””, American Biology
Teacher, Vol. 71, No. 2, pp. 81–83, February 2009.
1089. Ata Allah Taleizadeh, Seyed Taghi Akhavan Niaki and Mir-Bahador Aryanezhad, “A hybrid method of Pareto, TOPSIS and genetic algorithm to optimize multi-product multi-constraint inventory control systems with random fuzzy
replenishments”, Mathematical and Computer Modelling, Vol. 49, Nos. 5-6, pp. 1044–1057, March 2009.
1090. S. Afshin Mansouri, S. Hamed Hendizadeh and Nasser Salmasi, “Bicriteria scheduling of a two-machine flowshop with
sequence-dependent setup times”, International Journal of Advanced Manufacturing Technology, Vol. 40, Nos. 11–12,
pp. 1216–1226, February 2009.
1091. Mohammed Shalaby and Kazuhiro Saitou, “High-Stiffness, Lock-and-Key Heat-Reversible Locator-Snap Systems for the
Design for Disassembly”, Journal of Mechanical Design, Vol. 131, No. 4, Article Number: 041005, April 2009.
1092. Matteo Nicolini and Luigino Zovatto, “Optimal Location and Control of Pressure Reducing Valves in Water Networks”,
Journal of Water Resources Planning and Management–ASCE, Vol. 135, No. 3, pp. 178–187, May-June 2009.
1093. Mohammed M. Shalaby, Zhongde Wang, Linda L-W. Chow, Brian D. Jensen, John L. Volakis, Katsuo Kurabayashi and
Kazuhiro Saitou, “Robust Design of RF-MEMS Cantilever Switches Using Contact Physics Modeling”, IEEE Transactions on Industrial Electronics, Vol. 56, No. 4, pp. 1012–1021, April 2009.
1094. Y. Shi and R.D. Reitz, “Optimization study of the effects of bowl geometry, spray targeting, and swirl ratio for a
heavy-duty diesel engine operated at low and high load”, International Journal of Engine Research, Vol. 9, No. 4, pp.
325–346, August 2008.
1095. Alexandre M. Baltar and Darrell G. Fontane, “Use of multiobjective particle swarm optimization in water resources
management”, Journal of Water Resources Planning and Management–ASCE, Vol. 134, No. 3, pp. 257–265, May-June
2008.
1096. M.A. Elsays, M. Naguib Aly and A.A. Badawi, “Optimizing the dynamic response of the H. B. Robinson nuclear plant
using multiobjective particle swarm optimization”, Kerntechnik, Vol. 74, Nos. 1–2, pp. 70–78, April 2009.
1097. Rodolfo Dufo-Lopez and Jose L. Bernal-Agustin, “Multi-objective design of PV-wind-diesel-hydrogen-battery systems”,
Renewable Energy, Vol. 33, No. 12, pp. 2559–2572, December 2008.
1098. Asish Kumar Sharma, Chandramouli Kulshreshtha and Kee-Sun Sohn, “Discovery of New Green Phosphors and Minimization of Experimental Inconsistency Using a Multi-Objective Genetic Algorithm-Assisted Combinatorial Method”,
Advanced Functional Materials, Vol. 19, No. 11, pp. 1705–1712, June 9, 2009.
53
1099. Franklin Mendoza, Jose L. Bernal-Agustin and Jose A. Dominguez-Navarro, “NSGA and SPEA applied to multiobjective
design of power distribution systems”, IEEE Transactions on Power Systems, Vol. 21, No. 4, pp. 1938–1945, November
2006.
1100. G.N. Beligiannis, C. Moschopoulos, S.D. Likothanassis, “A genetic algorithm approach to school timetabling”, Journal
of the Operational Research Society, Vol. 60, No. 1, pp. 23–42, January 2009.
1101. Benjamin Torben-Nielsen and Klaus M. Stiefel, “Systematic mapping between dendritic function and structure”, NetworkComputation in Neural Systems, Vol. 20, No. 2, pp. 59–105, 2009.
1102. J. Branke, B. Scheckenbach, M. Stein, K. Deb and H. Schmeck, “Portfolio optimization with an envelope-based multiobjective evolutionary algorithm”, European Journal of Operational Research, Vol. 199, No. 3, pp. 684–693, December
16, 2009.
1103. A.G. Lopez-Herrera, E. Herrera-Viedma and F. Herrera, “Applying multi-objective evolutionary algorithms to the automatic learning of extended Boolean queries in fuzzy ordinal linguistic information retrieval systems”, Fuzzy Sets and
Systems, Vol. 160, No. 15, pp. 2192–2205, August 1, 2009.
1104. Antonio Nebro, Juan J. Durillo, Francisco Luna, Bernabé Dorronsoro and Enrique Alba, “MOCell: A Cellular Genetic
Algorithm for Multiobjective Optimization”, International Journal of Intelligent Systems, Vol. 24, No. 7, pp. 726–746,
July 2009.
1105. Ricardo Brunelli and Christian von L¨
ucken, “Optimal Crop Selection Using Multiobjective Evolutionary Algorithms”,
AI Magazine, Vol. 30, No. 2, pp. 96–105, Summer 2009.
1106. Brahim Aghezzaf and Mohamed Naimi, “The two-stage recombination operator and its application to the multiobjective
0/1 knapsack problem: A comparative study”, Computers & Operations Research, Vol. 36, No. 12, pp. 3247–3262,
December 2009.
1107. J.M. Herrero, S. Garcia-Nieto, X. Blasco, V. Romero-Garcia, J.V. Sanchez-Perez, L.M. Garcia-Raffi, “Optimization of
sonic crystal attenuation properties by ev-MOGA multiobjective evolutionary algorithm”, Structural and Multidisciplinary Optimization, Vol. 39, No. 2, pp. 203–215, August 2009.
1108. Maria Jose Gacto, Rafael Alcala and Francisco Herrera, “Adaptation and application of multi-objective evolutionary
algorithms for rule reduction and parameter tuning of fuzzy rule-based systems”, Soft Computing, Vol. 13, No. 5, pp.
419–436, March 2009.
1109. R. Alcala, M.J. Gacto, F. Herrera and J. Alcala-Fdez, “A multi-objective genetic algorithm for tuning and rule selection
to obtain accurate and compact linguistic fuzzy rule-based systems”, International Journal of Uncertainty Fuzziness and
Knowledge-Based Systems, Vol. 15, No. 5, pp. 539–557, October 2007.
1110. Dimo Brockhoff, Tobias Friedrich, Nils Hebbinghaus, Christian Klein, Frank Neumann and Eckart Zitzler, “On the
Effects of Adding Objectives to Plateau Functions”, IEEE Transactions on Evolutionary Computation, Vol. 13, No. 3,
pp. 591–603, July 2009.
1111. Shashi Mittal and Kalyanmoy Deb, “Optimal Strategies of the Iterated Prisoner’s Dilemma Problem for Multiple Conflicting Objectives”, IEEE Transactions on Evolutionary Computation, Vol. 13, No. 3, pp. 554–565, July 2009.
1112. A.G. Lopez-Herrera, E. Herrera-Viedma and F. Herrera, “A Study of the Use of Multi-Objective Evolutionary Algorithms to Learn Boolean Queries: A Comparative Study”, Journal of the American Society for Information Science and
Technology, Vol. 60, No. 6, pp. 1192–1207, June 2009.
1113. Yeboon Yun, Min Yoon and Hirotaka Nakayama, “Multi-objective optimization based on meta-modeling by using support
vector regression”, Optimization and Engineering, Vol. 10, No. 2, pp. 167–181, June 2009.
1114. V. Romero-Garcia, J.V. Sanchez-Perez, L.M. Garcia-Raffi, J.M. Herrero, S. Garcia-Nieto and X. Blasco, “Hole distribution in phononic crystals: Design and optimization”, Journal of the Acoustical Society of America, Vol. 125, No. 6, pp.
3774–3783, June 2009.
1115. Eduardo Fernandez, Jorge Navarro and Sergio Bernal, “Multicriteria sorting using a valued indifference relation under a
preference disaggregation paradigm”, European Journal of Operational Research, Vol. 198, No. 2, pp. 602–609, October
16, 2009.
1116. Dimo Brockhoff and Eckart Zitzler, “Objective Reduction in Evolutionary Multiobjective Optimization: Theory and
Applications”, Evolutionary Computation, Vol. 17, No. 2, pp. 135–166, Summer 2009.
1117. Annette Chmielewski, Boris Naujoks, Michael Janas and Uwe Clausen, “Optimizing the Door Assignment in LTLTerminals”, Transportation Science, Vol. 43, No. 2, pp. 198–210, May 2009.
1118. H.C.W. Lau, T.M. Chan, W.T. Tsui, F.T.S. Chan, G.T.S. Ho, K.L. Choy, “A fuzzy guided multi-objective evolutionary
algorithm model for solving transportation problem”, Expert Systems with Applications, Vol. 36, No. 4, pp. 8255–8268,
May 2009.
1119. Carlos Henggeler Antunes, Dulce Fernao Pires, Carlos Barrico, Alvaro Gomes and Antonio Gomes Martins, “A multiobjective evolutionary algorithm for reactive power compensation in distribution networks”, Applied Energy, Vol. 86,
Nos. 7–8, pp. 977–984, July-August 2009.
54
1120. Dongdong Yang, Licheng Jiao and Maoguo Gong, “Adaptive Multi-Objective Optimization Based on Nondominated
Solutions”, Computational Intelligence, Vol. 25, No. 2, pp. 84–108, May 2009.
1121. V. Romero-Garcia, J.V. Sanchez-Perez, L.M. Garcia-Raffi, J.M. Herrero, S. Garcia-Nieto and X. Blasco, “High optimization process for increasing the attenuation properties of acoustic metamaterials by means of the creation of defects”,
Applied Physics Letters, Vol. 93, No. 22, Article Number: 223502, December 1, 2008.
Cap´ıtulos de Libros
• Guillermo Leguizam´
on and Carlos A. Coello Coello, “Multi-Objective Ant Colony Optimization: A Taxonomy
and Review of Approaches”, in Satchidanada Dehuri, Susmita Ghosh and Sung Bae Cho (editors), Integration
of Swarm Intelligence and Artificial Neural Network, Chapter 3, pp. 67–94, World Scientific, Singapore, 2011,
ISBN 978-981-4280-14-3.
1. Ruby L.V. Moritz, Enrico Reich, Maik Schwarz, Matthias Bernt and Martin Middendorf, “Refined ranking relations for
selection of solutions in multi objective metaheuristics”, European Journal of Operational Research, Vol. 243, No. 2, pp.
454–464, June 1, 2015.
• Juan Carlos Fuentes Cabrera and Carlos A. Coello Coello, “Micro-MOPSO: A Multi-Objective Particle
Swarm Optimizer that Uses a Very Small Population Size”, in Nadia Nedjah, Leandro dos Santos Coelho and
Luiza de Macedo de Mourelle (editors), Multi-Objective Swarm Intelligent Systems. Theory & Experiences,
Chapter 4, pp. 83–104, Springer, Berlin, Germany, 2010, ISBN 978-3-642-05164-7.
1. T. Krausse, J. Cullmann, P. Saile and G.H. Schmitz, “Robust multi-objective calibration strategies - possibilities for
improving flood forecasting”, Hydrology and Earth System Sciences, Vol. 16, No. 10, pp. 3579–3606, 2012.
• Alfredo Arias Monta˜
no, Carlos A. Coello Coello and Efr´
en Mezura-Montes, “Evolutionary Algorithms Applied to Multi-Objective Aerodynamic Shape Optimization”, in Slawomir Koziel and Xin-She Yang (editors),
Computational Optimization, Methods and Algorithms, Chapter 10, pp. 211–240, Springer, Berlin, Germany,
2011, ISBN 978-3-642-20858-4.
1. Amir Nejat, Pooya Mirzabeygi and Masoud Shariat Panahi, “Airfoil shape optimization using improved Multiobjective
Territorial Particle Swarm algorithm with the objective of improving stall characteristics”, Structural and Multidisciplinary Optimization, Vol. 49, No. 6, pp. 953–967, June 2014.
2. Ni Li, Zeya Su, Zhuming Bi, Chao Tian, Zhiming Ren and Guanghong Gong, “A supportive architecture for CFD-based
design optimisation”, Enterprise Information Systems, Vol. 8, No. 2, pp. 246–278, March 4, 2014.
• Carlos A. Coello Coello, “An Introduction to Multi-Objective Particle Swarm Optimizers”, in Ant´
onio
Gaspar-Cunha, Ricardo Takahashi, Gerald Schaefer and Lino Costa (editors), Soft Computing in Industrial Applications, pp. 3–12, Springer, Advances in Intelligent and Soft Computing Series, Vol. 96, Berlin,
2011, ISBN 978-3-642-20504-0.
Number: 1450002, April 2014.
• Luis V. Santana-Quintero, Alfredo Arias Monta˜
no and Carlos A. Coello Coello, “A Review of Techniques
for Handling Expensive Functions in Evolutionary Multi-Objective Optimization”, in Yoel Tenne and ChiKeong Goh (editors), Computational Intelligence in Expensive Optimization Problems, Chapter 2, pp. 29–59,
Springer, Berlin, Germany, 2010, ISBN 978-3-642-10700-9.
1. Luc Wismans, Eric Van Berkum and Michiel Bliemer, “Acceleration of Solving the Dynamic Multi-Objective Network
Design Problem Using Response Surface Methods”, Journal of Intelligent Transporation Systems, Vol. 18, No. 1, pp.
17–29, January 2, 2014.
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3. Alexandru-Ciprian Zavoianu, Gerd Bramerdorfer, Edwin Lughofer, Siegfried Silber, Wolfgang Amrhein and Erich Peter
Klement, “Hybridization of multi-objective evolutionary algorithms and artificial neural networks for optimizing the
performance of electrical drives”, Engineering Applications of Artificial Intelligence, Vol. 26, No. 8, pp. 1781–1794,
September 2013.
4. Jiandao Zhu, Yi-Jen Wang and Matthew Collette, “A multi-objective variable-fidelity optimization method for genetic
algorithms”, Engineering Optimization, Vol. 46, No. 4, pp. 521–542, April 3, 2014.
5. Rommel G. Regis, “Constrained optimization by radial basis function interpolation for high-dimensional expensive blackbox problems with infeasible initial points”, Engineering Optimization, Vol. 46, No. 2, pp. 218–243, February 1, 2014.
6. Tsung-Che Chiang, “Enhancing rule-based scheduling in wafer fabrication facilities by evolutionary algorithms: Review
and opportunity”, Computers & Industrial Engineering, Vol. 64, No. 1, pp. 524–535, January 2013.
7. Minh Nghia Le, Yew Soon Ong, Stefan Menzel, Yaochu Jin and Bernhard Sendhoff, “Evolution by Adapting Surrogates”,
Evolutionary Computation, Vol. 21, No. 2, pp. 313–340, Summer 2013.
• Carlos A. Coello Coello, Clarisse Dhaenens and Laetitia Jourdan, “Multi-Objective Combinatorial Optimization: Problematic and Context”, in Carlos A. Coello Coello, Clarisse Dhaenens and Laetitia Jourdan
(editors), Advances in Multi-Objective Nature Inspired Computing, pp. 1–21, Springer, Berlin, Studies in
Computational Intelligence Vol. 272, 2010, ISBN 978-3-642-11217-1.
1. I-Tung Yang, Yo-Ming Hsieh and Li-Ou Kung, “Parallel Computing Platform for Multiobjective Simulation Optimization
of Bridge Maintenance Planning”, Journal of Construction Engineering and Management–ASCE, Vol. 138, No. 2, pp.
215–226, February 2012.
• Efr´
en Mezura-Montes, Luc´ıa Mu˜
noz-D´
avila and Carlos A. Coello Coello, “A Preliminary Study of Fitness Inheritance in Evolutionary Constrained Optimization”, in Natalio Krasnogor, Giuseppe Nicosia, Mario Pavone
and David Pelta (editors), Nature Inspired Cooperative Strategies for Optimization, pp. 1–14, Springer,
Berlin, Germany, 2008, ISBN 978-3-540-78986-4.
• Julio Barrera and Carlos A. Coello Coello, “A Review of Particle Swarm Optimization Methods used for Multimodal Optimization”, in Chee-Peng Lim, Lakhmi C. Jain and Satchidananda Dehuri (editors), Innovations
in Swarm Intelligence, Chapter 2, pp. 9–37, Springer-Verlag, Berlin, Germany, 2009, ISBN 978-3-642-042256.
1. Joshua T. Knight, Frank T. Zahradka, David J. Singer and Matthew D. Collette, “Multiobjective Particle Swarm
Optimization of a Planing Craft with Uncertainty”, Journal of Ship Production and Design, Vol. 30, No. 4, pp.
194–200, November 2014.
2. Kalyanmoy Deb and Nikhil Padhye, “Enhancing performance of particle swarm optimization through an algorithmic
link with genetic algorithms”, Computational Optimization and Applications, Vol. 57, No. 3, pp. 761–794, April 2014.
3. Aniruddha Basak, Swagatam Das and Kay Chen Tan, “Multimodal Optimization Using a Biobjective Differential Evolution Algorithm Enhanced With Mean Distance-Based Selection”, IEEE Transactions on Evolutionary Computation,
Vol. 17, No. 5, pp. 666–685, October 2013.
4. Kalyanmoy Deb and Amit Saha, “Multimodal Optimization Using a Bi-Objective Evolutionary Algorithm”, Evolutionary
Computation, Vol. 20, No. 1, pp. 27–62, Spring 2012.
• Ruhul Sarker and Carlos A. Coello Coello, “Assessment Methodologies for Multiobjective Evolutionary
Algorithms”, in Ruhul Sarker, Masoud Mohammadian and Xin Yao (Editores), Evolutionary Optimization,
Chapter 7, pp. 177–195, Kluwer Academic Publishers, Boston, USA, February 2002, ISBN 0-7923-7654-4.
III Analysis of the results”, Polish Maritime Research, Vol. 18, No. 4, pp. 3–13, 2011.
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• El-Ghazali Talbi, Sanaz Mostaghim, Tatsuya Okabe, Hisao Ishibuchi, G¨
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Coello, “Parallel Approaches for Multi-objective Optimization”, in J¨
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1. Steffen Limmer and Dietmar Fey, “Porting of the transfer-matrix method for multilayer thin-film computations on
graphics processing units”, Optical Engineering, Vol. 52, No. 7, Article Number: 075103, July 2013.
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2. Danilo Vasconcellos Vargas, Junichi Murata, Hirotaka Takano and Alexandre Claudio Botazzo Delbem, “General Subpopulation Framework and Taming the Conflict Inside Populations”, Evolutionary Computation, Vol. 23, No. 1, pp.
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5. Bilel Derbel, Jeremie Humeauc, Arnaud Liefooghe and Sebastien Verel, “Distributed localized bi-objective search”,
European Journal of Operational Research, Vol. 239, No. 3, pp. 731–743, December 16, 2014.
7. Matjaz Depolli, Roman Trobec and Bogdan Filipic, “Asynchronous Master-Slave Parallelization of Differential Evolution
for Multi-Objective Optimization”, Evolutionary Computation, Vol. 21, No. 2, pp. 261–291, Summer 2013.
8. Van Vinh Nguyen, Dietrich Hartmann and Markus König, “A distributed agent-based approach for simulation-based
optimization”, Advanced Engineering Informatics, Vol. 26, No. 4, pp. 814–832, October 2012.
9. Christian Grimme, Joachim Lepping and Alexander Papaspyrou, “Parallel predator-prey interaction for evolutionary
multi-objective optimization”, Natural Computing, Vol. 11, No. 3, pp. 519–533, September 2012.
10. Nima Safaei, Dragan Banjevic and Andrew K.S. Jardine, “Multi-threaded simulated annealing for a bi-objective maintenance scheduling problem”, International Journal of Production Research, Vol. 50, No. 1, pp. 63–80, 2012.
11. Gualtiero Colombo and Stuart M. Allen, “A comparison of problem decomposition techniques for the FAP”, Journal of
Heuristics, Vol. 16, No. 3, pp. 259–288, June 2010.
12. Tomas Petkus, Ernestas Filatovas and Olga Kurasova, “Investigation of Human Factors while Solving Multiple Criteria
Optimization Problems in Computer Network”, Technological and Economic Development of Economy, Vol. 15, No. 3,
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• Antonio L´
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in Many-objective Evolutionary Algorithms”, in Raymond Chiong (editor), Nature-Inspired Algorithms for
Optimisation, Chapter 15, pp. 413–434, Springer, Berlin, Germany, 2009, ISBN 978-3-642-00266-3.
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• Margarita Reyes Sierra and Carlos A. Coello Coello, “A Study of Techniques to Improve the Efficiency of a
Multi-Objective Particle Swarm Optimizer”, in Shengxiang Yang, Yew Soon Ong and Yaochu Jin (editors),
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methods and measures”, Soft Computing, Vol. 15, No. 7, pp. 1427–1448, July 2011.
• Fabio Freschi, Carlos A. Coello Coello and Maurizio Repetto, “Multiobjective Optimization and Artificial
Immune Systems: A Review”, in Hongwei Mo (editor), Handbook of Research on Artificial Immune Systems
and Natural Computing: Applying Complex Adaptive Technologies, Chapter I, pp. 1–21, Medical Information
Science Reference, Hershey, USA, 2009, ISBN 978-1-60566-310-4.
2. Zhuhong Zhang and Shuqu Qian, “Artificial immune system in dynamic environments solving time-varying non-linear
constrained multi-objective problems”, Soft Computing, Vol. 15, No. 7, pp. 1333–1349, July 2011.
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using Differential Evolution: A Survey of the State-of-the-Art”, in Uday K. Chakraborty (editor), Advances
in Differential Evolution, Chapter 7, pp. 173–196, Springer-Verlag, Berlin, Germany, 2008, ISBN 978-3-54068827-3.
1. J.A. Adeyemo and O.O. Olofintoye, “Evaluation of Combined Pareto Multiobjective Differential Evolution on Tuneable
Problems”, International Journal of Simulation Modelling, Vol. 13, No. 3, pp. 276–287, September 2014.
4. Hu Xia, Jian Zhuang and Dehong Yu, “Combining Crowding Estimation in Objective and Decision Space With Multiple
Selection and Search Strategies for Multi-Objective Evolutionary Optimization”, IEEE Transactions on Cybernetics,
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Operation”, Journal of Computing in Civil Engineering, Vol. 27, No. 2, pp. 139–147, March 2013.
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9. Xiang Li and Gang Du, “BSTBGA: A hybrid genetic algorithm for constrained multi-objective optimization problems”,
Computers & Operations Research, Vol. 40, No. 1, pp. 282–302, January 2013.
10. P.M. Mateo and I. Alberto, “A mutation operator based on a Pareto ranking for multi-objective evolutionary algorithms”,
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in the power market”, Energy Conversion and Management, Vol. 57, pp. 13–22, May 2012.
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• Luis V. Santana-Quintero, Noel Ram´ırez-Santiago and Carlos A. Coello Coello, “Towards a More Efficient
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• Antonio L´
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of the State-of-the-Art and some of their Applications in Chemical Engineering”, in Rangaiah Gade Pandu
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2. J. Novo, M.G. Penedo and J. Santos, “Evolutionary multiobjective optimization of Topological Active Nets”, Pattern
Recognition Letters, Vol. 31, No. 13, pp. 1781–1794, October 1, 2010.
• Carlos A. Coello Coello, “Evolutionary Multi-Objective Optimization in Finance”, in Jean-Philippe Rennard
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3. Chao Song, Ming Liu, Jiannong Cao, Yuan Zheng, Haigang Gong and Guihai Chen, “Maximizing network lifetime
based on transmission range adjustment in wireless sensor networks”, Computer Communications, Vol. 32, No. 11, pp.
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with remembered Pareto set”, The International Journal of Advanced Manufacturing Technology, Vol. 37, Nos. 7–8, pp.
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• Carlos A. Coello Coello, “20 Years of Evolutionary Multi-Objective Optimization: What Has Been Done
and What Remains to be Done”, in Gary Y. Yen and David B. Fogel (editors), Computational Intelligence:
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2. Abhishek Singh, Barbara S. Minsker and Albert J. Valocchi, “An interactive multi-objective optimization framework for
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3. Pletari Pulkkinen, Jarmo Hytonen and Hannu Kolvisto, “Developing a bioaerosol detector using hybrid genetic fuzzy
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5. Parames Chutima and Palida Chimklai, “Multi-objective two-sided mixed-model assembly line balancing using particle
swarm optimisation with negative knowledge”, Computers & Industrial Engineering, Vol. 62, No. 1, pp. 39–55, February
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6. Lily Rachmawati and Dipti Srinivasan, “Incorporating the Notion of Relative Importance of Objectives in Evolutionary
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7. A.A. Aguilar-Lasserre, L. Pibouleau, C. Azzaro-Pantel and S. Domenech, “Enhanced genetic algorithm-based fuzzy
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8. Jingqiao Zhang and Arthur C. Sanderson, “JADE: Adaptive Differential Evolution with Optional External Archive”,
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• Carlos A. Coello Coello and Carlos E. Mariano Romero, “Evolutionary Algorithms and Multiple Objective
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3. Olcay Ersel Canyurt and Prabhat Hajela, “Cellular genetic algorithm technique for the multicriterion design optimization”, Structural and Multidisciplinary Optimization, Vol. 40, Nos. 1–6, pp. 201–214, January 2010.
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en Mezura-Montes and Carlos A. Coello Coello, “Constrained Optimization via Multiobjective Evolutionary Algorithms”, in Joshua Knowles, David Corne and Kalyanmoy Deb (Editors), Multi-Objective Problem
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3. Blaze Gjorgiev and Marko Cepin, “A multi-objective optimization based solution for the combined economic-environmental
power dispatch problem”, Engineering Applications of Artificial Intelligence, Vol. 26, No. 1, pp. 417–429, January 2013.
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Effects of Adding Objectives to Plateau Functions”, IEEE Transactions on Evolutionary Computation, Vol. 13, No. 3,
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Journals Internacionales
• Jorge E. Rodr´ıguez, Andr´
es L. Medaglia and Carlos A. Coello Coello, “Design of a motorcycle frame using
neuroacceleration strategies in MOEAs”, Journal of Heuristics, Vol. 15, No. 2, pp. 177–196, April 2009.
1. Joseph Y.J. Chow and Amelia C. Regan, “A surrogate-based multiobjective metaheuristic and network degradation
simulation model for robust toll pricing”, Optimization and Engineering, Vol. 15, No. 1, pp. 137–165, March 2014.
• Antonio L´
opez Jaimes and Carlos A. Coello Coello, “Including preferences into a multiobjective evolutionary
algorithm to deal with many-objective engineering optimization problems”, Information Sciences, Vol. 277,
pp. 1–20, September 1, 2014.
• Carlos A. Coello Coello, “Research Directions in Evolutionary Multi-Objective Optimization. Current and
Future Research Topics”, Transactions of the Japanese Society for Evolutionary Computation, Vol. 3, No.
3, pp. 110–121, December 2012.
1. Shahin Rostami, Dean O’Reilly, Alex Shenfield and Nicholas Bowring, “A novel preference articulation operator for the
Evolutionary Multi-Objective Optimisation of classifiers in concealed weapons detection”, Information Sciences, Vol.
295, pp. 494–520, February 20, 2015.
• Victoria S. Arag´
on, Susana C. Esquivel and Carlos A. Coello Coello, “A T-Cell Algorithm for Solving Dynamic
Optimization Problems”, Information Sciences, Vol. 181, No. 17, pp. 3614–3637, 1 September 2011.
63
1. Min Han, Chuang Liu and Jun Xing, “An evolutionary membrane algorithm for global numerical optimization problems”,
2. Motjabe Ghasemi, Mohammad Mehdi Ghanbarian, Sahand Ghavidel, Shima Rahmani and Esmaeil Mahboubi Moghaddam, “Modified teaching learning algorithm and double differential evolution algorithm for optimal reactive power
dispatch problem: A comparative study”, Information Sciences, Vol. 278, pp. 231–249, September 10, 2014.
3. Changhe Li, Thanh Nguyen Trung, Ming Yang, Shengxiang Yang and Sanyou Zeng, “Multi-population methods in
unconstrained continuous dynamic environments: The challenges”, Information Sciences, Vol. 296, pp. 95–118, March
1, 2015.
• D.A. Bloch and C.A. Coello Coello, “Smiling at Evolution”, Applied Soft Computing, Vol. 11, No. 8, pp.
5724–5734, December 2011.
1. Adam P. Piotrowski, “Differential Evolution algorithms applied to Neural Network training suffer from stagnation”,
Applied Soft Computing, Vol. 21, pp. 382–406, August 2014.
• Antonin Ponsich and Carlos A. Coello Coello, “A Hybrid Differential Evolution-Tabu Search Algorithm for
the Solution of Job-Shop Scheduling Problems”, Applied Soft Computing, Vol. 13, No. 1, pp. 462–474,
January 2013.
2. Hao Gao, Sam Kwong, Baojie Fan and Ran Wang, “A Hybrid Particle-Swarm Tabu Search Algorithm for Solving Job
Shop Scheduling Problems”, IEEE Transactions on Industrial Informatics, Vol. 10, No. 4, pp. 2044–2054, November
2014.
• Eduardo Fern´
andez, Edy L´
opez, Gustavo Mazcorro, Rafael Olmedo and Carlos A. Coello Coello, “Application
of the non-outranked sorting genetic algorithm to public project portfolio selection”, Information Sciences,
Vol. 228, pp. 131–149, 10 April 2013.
1. Serkan Altuntas and Turkay Dereli, “A novel approach based on DEMATEL method and patent citation analysis for
prioritizing a portfolio of investment projects”, Expert Systems with Applications, Vol. 42, No. 3, pp. 1003–1012,
February 15, 2015.
• Antonin Ponsich, Antonio L´
opez Jaimes and Carlos A. Coello Coello, “A Survey on Multiobjective Evolutionary Algorithms for the Solution of the Portfolio Optimization Problem and Other Finance and Economics
Applications”, IEEE Transactions on Evolutionary Computation, Vol. 17, No. 3, pp. 321–344, June 2013.
• Miguel A. Medina, Swagatam Das, Carlos A. Coello Coello, and Juan M. Ram´ırez, “Decomposition-based
Modern Metaheuristic Algorithms for Multi-Objective Optimal Power Flow–A Comparative Study”, Engineering Applications of Artificial Intelligence, Vol. 32, pp. 10–20, June 2014.
1. Krzysztof Michalak, “The effects of asymmetric neighborhood assignment in the MOEA/D algorithm”, Applied Soft
Computing, Vol. 25, pp. 97–106, December 2014.
• Carlos Segura, Carlos A. Coello Coello, Gara Miranda and Coromoto Le´
on, “Using Multi-objective Evolutionary Algorithms for Single-Objective Optimization”, 4OR–A Quarterly Journal of Operations Research,
Vol. 11, No. 3, pp. 201–228, September 2013.
1. Mario Garza-Fabre, Eduardo Rodriguez-Tello and Gregorio Toscano-Pulido, “Constraint-handling through multi-objective
optimization: The hydrophobic-polar model for protein structure prediction”, Computers & Operations Research, Vol.
53, pp. 128–153, January 2015.
2. Mohammad Amin Safarzadeh and Seyyed Mahdia Motahhari, “Co-optimization of carbon dioxide storage and enhanced
oil recovery in oil reservoirs using a multi-objective genetic algorithm (NSGA-II)”, Petroleum Science, Vol. 11, No. 3,
pp. 460–468, September 2014.
• Mario Villalobos-Arias, Gregorio Toscano Pulido and Carlos A. Coello Coello, “A New Mechanism to Maintain Diversity in Multi-Objective Metaheuristics”, Optimization, Vol. 61, No. 7, pp. 823–854, July 2012.
1. Nitin Narang, J.S. Dhillon and D.P. Kothari, “Weight pattern evaluation for multiobjective hydrothermal generation
scheduling using hybrid search technique”, International Journal of Electrical Power & Energy Systems, Vol. 62, pp.
665–678, November 2014.
64
• J.J. Durillo, A.J. Nebro, F. Luna, C.A. Coello Coello and E. Alba, “Convergence Speed in Multi-Objective
Metaheuristics: Efficiency Criteria and Empirical Study”, International Journal for Numerical Methods in
Engineering, Vol. 84, No. 11, pp. 1344–1375, 10 December, 2010.
1. Bin Zi, Huafeng Ding, Jianbin Cao, Zhencai Zhu and Andres Kecskemethy, “Integrated Mechanism Design and Control
for Completely Restrained Hybrid-Driven Based Cable Parallel Manipulators”, Journal of Intelligent & Robotic Systems,
Vol. 74, Nos. 3-4, pp. 643–661, June 2014.
2. Ngaarn J. Cheung and Hong-Bin Shen, “Hierarchical particle swarm optimizer for minimizing the non-convex potential
energy of molecular structure”, Journal of Molecular Graphics & Modelling, Vol. 54, pp. 114–122, November 2014.
3. Di Lu, Bende Wang, Yaodong Wang, Huicheng Zhou, Qiuhua Liang, Yong Peng and Tony Roskilly, “Optimal operation
of cascade hydropower stations using hydrogen as storage medium”, Applied Energy, Vol. 137, pp. 56–63, January 1,
2015.
5. F. Bourennani, S. Rahnamayan and G.F. Naterer, “Optimal Design Methods for Hybrid Renewable Energy Systems”,
International Journal of Green Energy, Vol. 12, No. 2, pp. 148–159, February 1, 2015.
6. Aris Lanaridis and Andreas Stafylopatis, “An artificial immune network for multiobjective optimization problems”,
Engineering Optimization, Vol. 46, No. 8, pp. 1008–1031, August 3, 2014.
• Oliver Sch¨
utze, Massimiliano Vasile and Carlos A. Coello Coello, “Computing the Set of epsilon-efficient
Solutions in Multi-Objective Space Mission Design”, Journal of Aerospace Computing, Information, and
Communication, Vol. 8, No. 3, pp. 53–70, March 2011.
1. Hu Xia, Jian Zhuang and Dehong Yu, “Multi-objective unsupervised feature selection algorithm utilizing redundancy
measure and negative epsilon-dominance for fault diagnosis”, Neurocomputing, Vol. 146, pp. 113–124, December 25,
2014.
Vol. 44, No. 3, pp. 378–393, March 2014.
• Gideon Avigad and Carlos A. Coello Coello, “Highly Reliable Optimal Solutions to Multi Objective Problems
and their Evolution by Means of Worst-case Analysis”, Engineering Optimization, Vol. 42, No. 1, pp. 1095–
1. Michael de Paly, Claudius M. Burger and Peter Bayer, “ Optimization under worst case constraints-a new global
multimodel search procedure”, Structural and Multidisciplinary Optimization, Vol. 48, No. 6, pp. 1153–1172, December
2013.
• Leticia Cecilia Cagnina, Susana Cecilia Esquivel and Carlos A. Coello Coello, “Solving Constrained Optimization Problems with a Hybrid Particle Swarm Optimization Algorithm”, Engineering Optimization, Vol.
43, No. 8, pp. 843–866, August 2011.
1. Kazuhiro Izui, Takayuki Yamada, Shinji Nishiwaki and Kazuto Tanaka, “Multiobjective optimization using an aggregative gradient-based method”, Structural and Multidisciplinary Optimization, Vol. 51, No. 1, pp. 173–182, January
2015.
2. Kedar Nath Das and Raghav Prasad Parouha, “An ideal tri-population approach for unconstrained optimization and
applications”, Applied Mathematics and Computation, Vol. 256, pp. 666–701, April 1, 2015.
3. Nantiwat Pholdee, Won-Woong Park, Dong-Kyu Kim, Yong-Taek Im, Sujin Bureerat, Hyuck-Cheol Kwon and MyungSik Chun, “Efficient hybrid evolutionary algorithm for optimization of a strip coiling process”, Engineering Optimization,
Vol. 47, No. 4, pp. 521–532, April 3, 2015.
4. Mostafa Z. Ali and Noor H. Awad, “A novel class of niche hybrid Cultural Algorithms for continuous engineering
optimization”, Information Sciences, Vol. 267, pp. 158–190, May 20, 2014.
March 2015.
6. Saber M. Elsayed, Ruhul A. Sarker and Efren Mezura-Montes, “Self-adaptive mix of particle swarm methodologies for
constrained optimization”, Information Sciences, Vol. 277, pp. 216–233, September 1, 2014.
7. Hossein Rajabalipour Cheshmehgaz, Md. Nazrul Islam and Mohammad Ishak Desa, “A polar-based guided multiobjective evolutionary algorithm to search for optimal solutions interested by decision-makers in a logistics network
design problem”, Journal of Intelligent Manufacturing, Vol. 25, No. 4, pp. 699-726, August 2014.
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8. Nantiwat Pholdee and Sujin Bureerat, “Hybrid real-code population-based incremental learning and approximate gradients for multi-objective truss design”, Engineering Optimization, Vol. 46, No. 8, pp. 1032–1051, August 3, 2014.
9. Yufei Zhuang and Haibin Huang, “Time-optimal trajectory planning for underactuated spacecraft using a hybrid particle
swarm optimization algorithm”, Acta Astronautica, Vol. 94, No. 2, pp. 690–698, February 2014.
10. Takashi Okamoto and Hironori Hirata, “Constrained optimization using a multipoint type chaotic Lagrangian method
with a coupling structure”, Engineering Optimization, Vol. 45, No. 3, pp. 311–336, March 1, 2013.
• Leticia Cecilia Cagnina, Susana Cecilia Esquivel and Carlos A. Coello Coello, “A Fast Particle Swarm Algorithm For Solving Smooth and Non-smooth Economic Dispatch Problems”, Engineering Optimization, Vol.
43, No. 5, pp. 485–505, May 2011.
1. Shunkui Ke, Doudou Guo, Qingliang Niu and Danfeng Huang, “Optimized production planning model for a multi-plant
cultivation system under uncertainty”, Engineering Optimization, Vol. 47, No. 2, pp. 204–220, February 1, 2015.
2. Yu-Jun Zheng, “Water wave optimization: A new nature-inspired metaheuristic”, Computers & Operations Research,
Vol. 55, pp. 1–11, March 2015.
3. Maoguo Gong, Qing Cai, Xiaowei Chen and Lijia Ma, “Complex Network Clustering by Multiobjective Discrete Particle
Swarm Optimization Based on Decomposition”, IEEE Transactions on Evolutionary Computation, Vol. 18, No. 1, pp.
82–97, February 2014.
4. Jiuping Xu, Ziqiang Zeng, Bernard Han and Xiao Lei, “A dynamic programming-based particle swarm optimization
algorithm for an inventory management problem under uncertainty”, Engineering Optimization, Vol. 45, No. 7, pp.
851–880, July 1, 2013.
• M. Davarynejad, C. W. Ahn, J. Vrancken, J. van den Berg and C. A. Coello Coello, “Evolutionary Hidden
Information Detection by Granulation-Based Fitness Approximation”, Applied Soft Computing, Vol. 10, No.
3, pp. 719–729, June 2010.
1. Yaochu Jin, “Surrogate-assisted evolutionary computation: Recent advances and future challenges”, Swarm and Evolutionary Computation, Vol. 1, No. 2, pp. 61–70, June 2011.
2. Luc Wismans, Eric Van Berkum and Michiel Bliemer, “Acceleration of Solving the Dynamic Multi-Objective Network
Design Problem Using Response Surface Methods”, Journal of Intelligent Transporation Systems, Vol. 18, No. 1, pp.
17–29, January 2, 2014.
3. Alexander E.I. Brownlee, John A.W. McCall and Qingfu Zhang, “Fitness Modeling With Markov Networks”, IEEE
4. Alexander E. Brownlee, Olivier Regnier-Coudert, John A.W. McCall, Stewart Massie and Stefan Stulajter, “An application of a GA with Markov network surrogate to feature selection”, International Journal of Systems Science, Vol. 44,
No. 11, pp. 2039–2056, November 1, 2013.
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178. Somayyeh Chamaani, S. Abdullah Mirtaheri and Mohammad S. Abrishamian, “Improvement of Time and Frequency
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128. S. Bureerat and S. Srisomporn, “Optimum plate-fin heat sinks by using a multi-objective evolutionary algorithm”,
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28. Andre Felipe Henriques Librantz, Nivaldo Lemos Coppini, Elesandro Antonio Baptista, Sidnei Alves de Araujo and
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Congresos Internacionales
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• Mario Garza-Fabre, Gregorio Toscano-Pulido, Carlos A. Coello Coello and Eduardo Rodr´ıguez-Tello, “Effective Ranking + Speciation = Many-Objective Optimization”, in 2011 IEEE Congress on Evolutionary
Computation (CEC’2011), pp. 2115–2122, IEEE Service Center, New Orleans, Louisiana, USA, 5-8 June,
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• Leticia C. Cagnina, Susana C. Esquivel and Carlos A. Coello Coello, “A Particle Swarm Optimizer for
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1. Mohsen Davarynejad, Jan van den Berg and Jafar Rezaei, “Evaluating center-seeking and initialization bias: The case of
particle swarm and gravitational search algorithms”, Information Sciences, Vol. 278, pp. 802–821, September 10, 2014.
• Elizabeth Montero, Mar´ıa-Cristina Riff, Leslie P´
erez-Caceres and Carlos A. Coello Coello, “Are State-of-theArt Fine-Tuning Algorithms Able to Detect a Dummy Parameter?”, in Carlos A. Coello Coello, Vincenzo
Cutello, Kalyanmoy Deb, Stephanie Forrest, Giuseppe Nicosia and Mario Pavone (Eds.), Parallel Problem
Solving from Nature - PPSN XII, 12th International Conference, pp. 306–315, Springer, Lecture Notes in
Computer Science Vol. 7491, Taormina, Italy, September 1-5, 2012, ISBN 978-3-642-32936-4.
1. Nasser R. Sabar, Masri Ayob, Graham Kendall and Rong Qu, “A Dynamic Multiarmed Bandit-Gene Expression Programming Hyper-Heuristic for Combinatorial Optimization Problems”, IEEE Transactions on Cybernetics, Vol. 45, No.
2, pp. 217–228, February 2015.
• Alfredo Arias-Monta˜
en Mezura-Montes, “Multi-Objective Airfoil Shape
Optimization Using a Multiple-Surrogate Approach”, in 2012 IEEE Congress on Evolutionary Computation
(CEC’2012), pp. 1188–1195, IEEE Press, Brisbane, Australia, June 10-15, 2012.
2014.
• Carlos A. Coello Coello, “Evolutionary Multi-Objective Optimization: Basic Concepts and Some Applications in Pattern Recognition”, in Jos´
e Francisco Mart´ınez-Trinidad, Jes´
us Ariel Carrasco-Ochoa, Cherif
Ben-Youssef Brants and Edwin Robert Hancock (Editors), Pattern Recognition, Third Mexican Conference,
MCPR 2011, pp. 22–33, Springer, Lecture Notes in Computer Science Vol. 6718, Cancun, M´
exico, June/July
2011.
“Physical programming for preference driven evolutionary multi-objective optimization”, Applied Soft Computing, Vol.
24, pp. 341–362, November 2014.
• Cynthia A. Rodr´ıguez Villalobos and Carlos A. Coello Coello, “A New Multi-Objective Evolutionary Algorithm Based on a Performance Assessment Indicator”, in 2012 Genetic and Evolutionary Computation
Conference (GECCO’2012), pp. 505–515, ACM Press, Philadelphia, USA, July 7-11, 2012, ISBN 978-14503-1177-9.
1. Jie Zeng and Wei Nie, “Novel multi-objective optimization algorithm”, Journal of Systems Engineering and Electronics,
Vol. 25, No. 4, pp. 697–710, August 2014.
• Mario Garza Fabre, Gregorio Toscano Pulido and Carlos A. Coello Coello, “Alternative Fitness Assignment Methods for Many-Objective Optimization Problems”, in Pierre Collet, Nicolas Monmarch´
e, Pierrick
Legrand, Marc Schoenauer and Evelyne Lutton (editors), Artificial Evolution, 9th International Conference,
Evolution Artificielle, EA 2009, pp. 146–157, Springer, Lecture Notes in Computer Science Vol. 5975,
Strasbourg, France, 2010.
454–464, June 1, 2015.
2. Ramprasad Joshi and Bharat Deshpande, “Empirical and analytical study of many-objective optimization problems:
analysing distribution of nondominated solutions and population size for scalability of randomized heuristics”, Memetic
Computing, Vol. 6, No. 2, pp. 133–145, June 2014.
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Vol. 18, No. 4, pp. 519–542, August 2014.
4. Zhenan He, Gary G. Yen and Jun Zhang, “Fuzzy-Based Pareto Optimality for Many-Objective Evolutionary Algorithms”,
• Adriana Lara L´
opez, Carlos A. Coello Coello and Oliver Schuetze, “A Painless Gradient-Assisted MultiObjective Memetic Mechanism for Solving Continuous Bi-objective Optimization Problems”, in 2010 IEEE
Congress on Evolutionary Computation (CEC’2010), pp. 577–584, IEEE Press, Barcelona, Spain, July 18–23,
2010.
1. Hyoungjin Kim and Meng-Sing Liou, “Adaptive directional local search strategy for hybrid evolutionary multiobjective
optimization”, Applied Soft Computing, Vol. 19, pp. 290–311, June 2014.
2. Honggang Wang, “Zigzag Search for Continuous Multiobjective Optimization”, INFORMS Journal on Computing, Vol.
25, No. 4, pp. 654–665, Fall 2013.
• Sa´
ul Zapotecas Mart´ınez and Carlos A. Coello Coello, “A Direct Local Search Mechanism for Decompositionbased Multi-Objective Evolutionary Algorithms”, in 2012 IEEE Congress on Evolutionary Computation
(CEC’2012), pp. 3431–3438, IEEE Press, Brisbane, Australia, June 10-15, 2012.
pp. 114–130, February 2014.
• Efr´
en Mezura-Montes and Carlos A. Coello Coello, “A Simple Evolution Strategy to Solve Constrained Optimization Problems”, in Erick Cant´
u-Paz et al. (editors), Genetic and Evolutionary Computation Conference—
GECCO’2003. Proceedings, Part I, Lecture Notes in Computer Science Vol. 2723, pp. 640–641, Springer,
Chicago, USA, July 2003.
en Mezura-Montes, “pMODE-LD+SS: A Parallel
Multi-Objective DE-based Algorithm”, in Robert Schaefer, Carlos Cotta, Joanna Kolodziej and G¨
unter
Rudolph (editors), Parallel Problem Solving from Nature–PPSN XI, 11th International Conference, Part II,
pp. 21–30, Springer, Lecture Notes in Computer Science Vol. 6239, Krakow, Poland, September 2010.
331–356, April 2013.
March 2015.
• Sa´
ul Zapotecas Mart´ınez and Carlos A. Coello Coello, “An Archive Strategy Based on the Convex Hull
of Individual Minima for MOEAs”, 2010 IEEE Congress on Evolutionary Computation (CEC’2010), pp.
912–919, IEEE Press, Barcelona, Spain, July 18–23, 2010.
• Antonio L´
opez Jaimes, Hern´
an Aguirre, Kiyoshi Tanaka and Carlos A. Coello Coello, “Objective Space
Partitioning Using Conflict Information for Many-objective Optimization”, in Robert Schaefer, Carlos Cotta,
Joanna Kolodziej and G¨
unter Rudolph (editors), Parallel Problem Solving from Nature–PPSN XI, 11th
International Conference, Part I, pp. 657–666, Springer, Lecture Notes in Computer Science Vol. 6238,
Krakow, Poland, September 2010.
1. Susmita Bandyopadhyay and Ranja Bhattacharya, “Solving a tri-objective supply chain problem with modified NSGA-II
algorithm”, Journal of Manufacturing Systems, Vol. 33, No. 1, pp. 41–50, January 2014.
199
• Sa´
ul Zapotecas Mart´ınez and Carlos A. Coello Coello, “A Multi-objective Particle Swarm Optimizer Based
on Decomposition”, in 2011 Genetic and Evolutionary Computation Conference (GECCO’2011), pp. 69–76,
ACM Press, Dublin, Ireland, July 12-16, 2011.
3. Yutao Qi, Xiaoliang Ma, Fang Liu, Licheng Jiao, Jianyong Sun and Jianshe Wu, “MOEA/D with Adaptive Weight
Adjustment”, Evolutionary Computation, Vol. 22, No. 2, pp. 231–264, Summer 2014.
47–77, Spring 2014.
• Antonio L´
opez Jaimes, Carlos A. Coello Coello, Hern´
an Aguirre and Kiyoshi Tanaka, “Adaptive Objective
Space Partitioning Using Conflict Information for Many-Objective Optimization”, in Ricardo H.C. Takahashi, Kalyanmoy Deb, Elizabeth F. Wanner and Salvatore Grecco (editors), Evolutionary Multi-Criterion
Optimization, 6th International Conference, EMO 2011, pp. 151–165, Springer. Lecture Notes in Computer
Science Vol. 6576, Ouro Preto, Brazil, April 2011.
1. Susmita Bandyopadhyay and Ranja Bhattacharya, “Solving a tri-objective supply chain problem with modified NSGA-II
algorithm”, Journal of Manufacturing Systems, Vol. 33, No. 1, pp. 41–50, January 2014.
• Mario Garza Fabre, Gregorio Toscano Pulido and Carlos A. Coello Coello, “Two Novel Approaches for ManyObjective Optimization”, 2010 IEEE Congress on Evolutionary Computation (CEC’2010), pp. 4480–4487,
IEEE Press, Barcelona, Spain, July 18–23, 2010.
• Mario Garza Fabre, Gregorio Toscano Pulido and Carlos A. Coello Coello, “Ranking Methods for ManyObjective Problems”, in Arturo Hern´
andez Aguirre, Ra´
ul Monroy Borja and Carlos Alberto Reyes Garc´ıa
(editors), MICAI 2009: Advances in Artificial Intelligence. 8th Mexican International Conference on Artificial Intelligence, pp. 633–645, Springer, Lecture Notes in Artificial Intelligence Vol. 5845, Guanajuato,
M´
exico, November 2009.
454–464, June 1, 2015.
3. Kalyanmoy Deb and Himanshu Jain, “An Evolutionary Many-Objective Optimization Algorithm Using Reference-PointBased Nondominated Sorting Approach, Part I: Solving Problems With Box Constraints”, IEEE Transactions on Evolutionary Computation, Vol. 18, No. 4, pp. 577–601, August 2014.
200
Vol. 18, No. 4, pp. 519–542, August 2014.
5. Zhenan He, Gary G. Yen and Jun Zhang, “Fuzzy-Based Pareto Optimality for Many-Objective Evolutionary Algorithms”,
248, pp. 191–213, November 1, 2013.
1602–1615, June 2013.
• Adriana Lara, Carlos A. Coello Coello and Oliver Sch¨
utze, “Using Gradient-Based Information to Deal with
Scalability in Multi-objective Evolutionary Algorithms”, in 2009 IEEE Congress on Evolutionary Computation (CEC’2009), pp. 16–23, IEEE Press, Trodheim, Norway, May 2009.
1. Ramprasad Joshi and Bharat Deshpande, “Empirical and analytical study of many-objective optimization problems:
analysing distribution of nondominated solutions and population size for scalability of randomized heuristics”, Memetic
Computing, Vol. 6, No. 2, pp. 133–145, June 2014.
248, pp. 191–213, November 1, 2013.
• Julio Barrera and Carlos A. Coello Coello, “A Particle Swarm Optimization Method for Multimodal Optimization Based on Electrostatic Interaction”, in Arturo Hern´
andez Aguirre, Ra´
ul Monroy Borja and Carlos
Alberto Reyes Garc´ıa (editors), MICAI 2009: Advances in Artificial Intelligence. 8th Mexican International Conference on Artificial Intelligence, pp. 622–632, Springer, Lecture Notes in Artificial Intelligence
Vol. 5845, Guanajuato, M´
1. Chaoli Sun, Jianchao Zeng, Jengshyang Pan, Songdong Xue and Yaochu Jin, “A new fitness estimation strategy for
particle swarm optimization”, Information Sciences, Vol. 221, pp. 355–370, February 1, 2013.
• Luis Vicente Santana-Quintero and Carlos A. Coello Coello, “An Algorithm Based on Differential Evolution
for Multiobjective Problems”, in Cihan H. Dagli, Anna L. Buczak, David L. Enke, Mark J. Embrechts and
Okan Ersoy (editors), Smart Engineering System Design: Neural Networks, Evolutionary Programming and
Artificial Life, Vol. 15, pp. 211–220, ASME Press, St. Louis, Missouri, USA, November 2005.
• Adriana Menchaca-Mendez and Carlos A. Coello Coello, “A New Proposal to Hybridize the Nelder-Mead
Method to a Differential Evolution Algorithm for Constrained Optimization”, in 2009 IEEE Congress on
Evolutionary Computation (CEC’2009), pp. 2598–2605, IEEE Press, Trodheim, Norway, May 2009.
53, pp. 128–153, January 2015.
2. Musrrat Ali, Millie Pant, Atulya K. Nagar and Chang Wook Ahn, “Two Local Search Strategies for Differential Evolution”, Journal of Universal Computer Science, Vol. 18, No. 13, pp. 1853–1870, 2012.
201
• Luis V. Santana-Quintero, Noel Ram´ırez and Carlos Coello Coello, “A Multi-Objective Particle Swarm Optimizer Hybridized with Scatter Search”, in Alexander Gelbukh and Carlos Alberto Reyes-Garc´ıa (Editors),
MICAI 2006: Advances in Artificial Intelligence, 5th International Conference in Artificial Intelligence,
Springer, pp. 294–304, Lecture Notes in Artificial Intelligence Vol. 4293, Apizaco, M´
1. Zhigang Ren, Aimin Zhang, Changyun Wen and Zuren Feng, “A Scatter Learning Particle Swarm Optimization Algorithm for Multimodal Problems”, IEEE Transactions on Cybernetics, Vol. 44, No. 7, pp. 1127–1140, July 2014.
3. Tao Zhang, W.A. Chaovalitwongse and Yuejie Zhang, “Scatter search for the stochastic travel-time vehicle routing
problem with simultaneous pick-ups and deliveries”, Computers & Operations Research, Vol. 39, No. 10, pp. 2277–2290,
October 2012.
en Mezura-Montes, “MODE-LD+SS: A Novel Differential Evolution Algorithm Incorporating Local Dominance and Scalar Selection Mechanisms for MultiObjective Optimization”, 2010 IEEE Congress on Evolutionary Computation (CEC’2010), pp. 3284–3291,
IEEE Press, Barcelona, Spain, July 18–23, 2010.
March 2015.
2012.
• V´ıctor Serrano, Mat´ıas Alvarado and Carlos A. Coello Coello, “Optimization to Manage Supply Chain
Disruptions Using the NSGA-II”, in Oscar Castillo, Patricia Melin, Oscar Montiel Ross, Roberto Sep´
ulveda
Cruz, Witold Pedrycz and Janusz Kacprzyk (editors), Theoretical Advances and Applications of Fuzzy Logic
and Soft Computing, pp. 476–485, Springer, 2007.
1. Jie Zhu, Xin Cai, Pan Pan and Rongrong Gu, “Multi-Objective Structural Optimization Design of Horizontal-Axis Wind
Turbine Blades Using the Non-Dominated Sorting Genetic Algorithm II and Finite Element Method”, Energies, Vol. 7,
No. 2, pp. 988–1002, February 2014.
2. N.C. Hiremath, Sadananda Sahu and Manoj Kuma Tiwari, “Multi objective outbound logistics network design for a
manufacturing supply chain”, Journal of Intelligent Manufacturing, Vol. 24, No. 6, pp. 1071–1084, December 2013.
3. Huanlai Xing and Rong Qu, “A nondominated sorting genetic algorithm for bi-objective network coding based multicast
routing problems”, Information Sciences, Vol. 233, pp. 36–53, June 1, 2013.
4. Hossein Rajabalipour Cheshmehgaz, Mohamad Ishak Desa and Antoni Wibowo, “A flexible three-level logistic network design considering cost and time criteria with a multi-objective evolutionary algorithm”, Journal of Intelligent
Manufacturing, Vol. 24, No. 2, pp. 277–293, April 2013.
5. S. Afshin Mansouri, David Gallear and Mohammad H. Askariazad, “Decision support for build-to-order supply chain
management through multiobjective optimization”, International Journal of Production Economics, Vol. 135, No. 1,
pp. 24–36, January 2012.
• Antonio J. Nebro, Juan J. Durillo, Jose Garcia-Nieto, Carlos A. Coello Coello, Francisco Luna and Enrique
Alba, “SMPSO: A New PSO-based Metaheuristic for Multi-objective Optimization”, in 2009 IEEE Symposium on Computational Intelligence in Multicriteria Decision-Making, pp. 66–73, IEEE Press, Nashville,
Tennessee, USA, March 30 - April 2, 2009.
1. Sofiene Kachroudi, Mathieu Grossard and Neil Abroug, “Predictive Driving Guidance of Full Electric Vehicles Using
Particle Swarm Optimization”, IEEE Transactions on Vehicular Technology, Vol. 61, No. 9, pp. 3909–3919, November
2012.
2. Sandra Garcia, David Quintana, InS M. Galvan and Pedro Isasi, “Extended mean-variance model for reliable evolutionary
portfolio optimization”, AI Communications, Vol. 27, No. 3, pp. 315–324, 2014.
202
5. Shuai Wang, Shaukat Ali and Arnaud Gotlieb, “Cost-effective test suite minimization in product lines using search
techniques”, Journal of Systems and Software, Vol. 103, pp. 370–391, May 2015.
9. Amin Ibrahim, Shahryar Rahnamayan, Miguel Vargas Martin and Bekir Yilbas, “Multi-objective thermal analysis of a
thermoelectric device: Influence of geometric features on device characteristics”, Energy, Vol. 77, pp. 305–317, December
1, 2014.
11. Kian Sheng Lim, Salinda Buyamin, Anita Ahmad, Mohd Ibrahim Shapiai, Faradila Naim, Marizan Mubin and Dong
Hwa Kim, “Improving Vector Evaluated Particle Swarm Optimisation Using Multiple Nondominated Leaders”, Scientific
12. Immanuel Trummer, Boi Faltings and Walter Binder, “Multi-Objective Quality-Driven Service Selection-A Fully Polynomial Time Approximation Scheme”, IEEE Transactions on Software Engineering, Vol. 40, No. 2, pp. 167–191, February
2014.
13. Roman Stryczek and Boguslaw Pytlak, “Multi-Objective Optimization with Adjusted PSO Method on Example of
Cutting Process of Hardened 18CrMo4 Steel”, Eksploatacja Niezawodnosc–Maintenance and Reliability, No. 1, pp.
236–245, 2014.
15. Eduardo J. Solteiro Pires, Jose A. Tenreiro Machado and Paulo B. de Moura Oliveira, “Entropy Diversity in MultiObjective Particle Swarm Optimization”, Entropy, Vol. 15, No. 12, pp. 5475–5491, December 2013.
16. Jun Guo, Jianzhong Zhou, Qiang Zou, Yi Liu and Lixiang Song, “A Novel Multi-Objective Shuffled Complex Differential
Evolution Algorithm with Application to Hydrological Model Parameter Optimization”, Water Resources Management,
Vol. 27, No. 8, pp. 2923–2946, June 2013.
17. Sandra Garcia, David Quintana, Ines M. Galvan and Pedro Isasi, “Multiobjective Algorithms with Resampling for
Portfolio Optimization”, Computing and Informatics, Vol. 32, No. 4, pp. 777–796, 2013.
19. Xianpeng Wang and Lixin Tang, “ Multiobjective Operation Optimization of Naphtha Pyrolysis Process Using Parallel
2013.
21. Youcef Bouchebaba, Ali-Erdem Ozcan, Pierre Paulin and Gabriela Nicolescu, “MpAssign: a framework for solving the
many-core platform mapping problem”, Software–Practice & Experience, Vol. 42, No. 7, pp. 891–915, July 2012.
January 1, 2012.
• Oliver Sch¨
utze, El-Ghazali Talbi, Carlos Coello Coello and Luis Vicente Santana-Quintero, “A Memetic
PSO Algorithm for Scalar Optimization Problems”, in Proceedings of the 2007 IEEE Swarm Intelligence
Symposium (SIS 2007), pp. 128–134, IEEE Press, Honolulu, Hawaii, USA, April 2007.
1. Hongfeng Wang, Ilkyeong Moon, Shenxiang Yang and Dingwe Wang, “A memetic particle swarm optimization algorithm
for multimodal optimization problems”, Information Sciences, Vol. 197, pp. 38–52, August 15, 2012.
203
• Alfredo G. Hernandez-Diaz, Carlos A. Coello Coello, Luis V. Santana-Quintero, Fatima Perez, Julian Molina
and Rafael Caballero, “On the use of Projected Gradients for Constrained Multiobjective Optimization
Problems”, in G¨
unter Rudolph, Thomas Jansen, Simon Lucas, Carlo Poloni and Nicola Beume (editors),
Parallel Problem Solving from Nature–PPSN X, pp. 712–721, Springer, Lecture Notes in Computer Science
Vol. 5199, Dortmund, Germany, September 2008.
1. Gang Yu, Tianyou Chai and Xiaochuan Luo, “Multiobjective Production Planning Optimization Using Hybrid Evolutionary Algorithms for Mineral Processing”, IEEE Transactions on Evolutionary Computation, Vol. 15, No. 4, pp.
487–514, August 2011.
• Antonio L´
opez Jaimes and Carlos A. Coello Coello, “Study of Preference Relations in Many-Objective
Optimization”, in 2009 Genetic and Evolutionary Computation Conference (GECCO’2009), pp. 611–618,
ACM Press, Montreal, Canada, July 8–12, 2009, ISBN 978-1-60558-325-9.
January 1, 2012.
• Oliver Schuetze, Carlos A. Coello Coello, Emilia Tantar and El-Ghazali Talbi, “Computing Finite Size Representations of the Set of Approximate Solutions of an MOP with Stochastic Search Algorithms”, in 2008
Genetic and Evolutionary Computation Conference (GECCO’2008), pp. 713–720, ACM Press, Atlanta,
USA, July 2008, ISBN 978-1-60558-131-6.
2011.
on, Susana C. Esquivel and Carlos A. Coello Coello, “A Novel Model of Artificial Immune
System for Solving Constrained Optimization Problems with Dynamic Tolerance Factor”, in Alexander Gel´
bukh and Angel
Fernando Kuri Morales (editors), MICAI 2007: Advances in Artificial Intelligence, 6th
International Conference on Artificial Intelligence, pp. 19–29, Springer, Lecture Notes in Artificial Intelligence Vol. 4827, Aguascalientes, M´
• Efr´
en Mezura Montes and Carlos A. Coello Coello, “Useful Infeasible Solutions in Engineering Optimization
´
with Evolutionary Algorithms”, in Alexander Gelbukh

Citations to Publications of Dr. Carlos A. Coello Coello that appear

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