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

Tesis Doctoral
Citations to Publications of
Dr. Carlos A. Coello Coello
that appear in the ISI Web of Science.
The total of citations (excluding self-citations) is 3566.
• 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. 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.
2. 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.
3. Hamit Saruhan, “Pivoted-pad journal bearings lubrication design”, Industrial Lubrication and Tribology, Vol. 63, Nos.
2-3, pp. 119–126, 2011.
4. Mark A. Gammon, “Optimization of fishing vessels using a Multi-Objective Genetic Algorithm”, Ocean Engineering,
Vol. 38, No. 10, pp. 1054–1064, July 2011.
5. 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.
6. 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.
7. 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.
8. 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.
9. 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.
10. 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.
11. 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.
12. 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.
13. 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.
14. 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.
15. 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.
16. 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.
17. 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.
1

18. 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.
19. C. Elegbede, “Structural reliability assessment based on particles swarm optimization”, Structural Safety, Vol. 27, No.
2, pp. 171–186, 2005.
20. Adil Baykasoˇglu, “Preemptive goal programming using simulated annealing”, Engineering Optimization, Vol. 37, No. 1,
pp. 49–63, January 2005.
21. 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.
22. 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.
23. 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.
24. Balram Suman, “Simulated Annealing-Based Multiobjective Algorithms and Their Application for System Reliability”,
Engineering Optimization, Vol. 35, No. 4, pp. 391–416, August 2003.
25. 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.
26. 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.
27. Johan Andersson and David Wallace, “Pareto optimization using the struggle genetic crowding algorithm”, Engineering
Optimization, Vol. 34, No. 6, pp. 623–643, December 2002.
28. 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.
29. 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.
30. 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.
31. 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.
32. 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.
33. A. Baykasoglu, “Goal programming using multiple objective tabu search”, Journal of the Operational Research Society,
Vol. 52, No. 12, pp. 1359–1369, December 2001.
34. 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.
35. 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.
36. Matthias Ehrgott and Xavier Gandibleux, “A Survey and Annotated Bibliography of Multiobjective Combinatorial
Optimization”, OR Spektrum, Vol. 22, pp. 425–460, 2000.
37. 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.
38. J. Olvander, “Robustness considerations in multi-objective optimal design”, Journal of Engineering Design, Vol. 16, No.
5, pp. 511–523, October 2005.
39. 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.
40. 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 Hernández 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.
2

Libros
41. 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.
42. 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.
• 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. 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.
2. 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.
3. 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.
4. 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.
5. 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.
6. 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.
7. 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,
April 11, 2012.
8. 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.
9. 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,
No. 8, pp. 1420–1425, August 2012.
10. Roberto Santana, Concha Bielza and Pedro Larrañaga, “Regularized logistic regression and multiobjective variable
selection for classifying MEG data”, Biological Cybernetics, Vol. 106, Nos. 6–7, pp. 389–405, September 2012.
11. Carolina Almeida, Richard A. Goncalves, Elizabeth F. Goldbarg, Marco C. Goldbarg and Myriam R. Delgado, “An
experimental analysis of evolutionary heuristics for the biobjective traveling purchaser problem”, Annals of Operations
Research, Vol. 199, No. 1, pp. 305–341, October 2012.
12. 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,
Vol. 391, No. 22, pp. 5490–5499, November 15, 2012.
13. 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,
December 2012.
14. 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.
15. 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.
16. 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,
July 2012.
3

17. Anthony Gerard Scanlan and Mark Keith Halton, “Hierarchical synthesis system with hybrid DLO-MOGA optimization”,
COMPEL–The International Journal for Computation and Mathematics in Electrical and Electronic Engineering, Vol.
30, No. 2, pp. 741–761, 2011.
18. Gustavo Olague and Leonardo Trujillo, “Interest point detection through multiobjective genetic programming”, Applied
Soft Computing, Vol. 12, No. 8, pp. 2566–2582, August 2012.
19. 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.
20. Vicent Romero-Garcia, Juan Sanchez-Perez and Luis Miguel Garcia-Raffi, “Molding the Acoustic Attenuation in Quasi-
Ordered Structures: Experimental Realization”, Applied Physics Express, Vol. 5, No. 8, Article Number: 087301,
August 2012.
21. Pankaj Rajak, Sudipto Ghosh, Baidurya Bhattacharya and Nirupam Chakraborti, “Pareto-optimal analysis of Zn-coated
Fe in the presence of dislocations using genetic algorithms”, Computational Materials Science, Vol. 62, pp. 266–271,
September 2012.
22. 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.
23. 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.
24. Anne Auger, Johannes Bader, Dimo Brockhoff and Eckart Zitzler, “Hypervolume-based multiobjective optimization:
Theoretical foundations and practical implications”, Theoretical Computer Science, Vol. 425, pp. 75–103, March 30,
2012.
25. 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.
26. 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:
692593, 2012.
27. 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.
28. Reinhard Koenig and Sven Schneider, “Hierarchical structuring of layout problems in an interactive evolutionary layout
system”, AI EDAM-Artificial Intelligence for Engineering Design Analysis and Manufacturing, Vol. 26, No. 2, pp.
129–142, May 2012.
29. 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.
30. 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.
31. 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.
32. 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”,
Reliability Engineering & System Safety, Vol. 103, pp. 35–44, July 2012.
33. 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
2012.
34. Renan S. Maciel, Mauro Rosa, Vladimiro Miranda and Antonio Padilha-Feltrin, “Multi-objective evolutionary particle
swarm optimization in the assessment of the impact of distributed generation”, Electric Power Systems Research, Vol.
89, pp. 100–108, August 2012.
35. 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.
36. 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.
37. 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,
Vol. 183, No. 5, pp. 1139–1154, May 2012.
4

38. 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,
pp. 213–223, May 2012.
39. 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.
57, No. 2, pp. 222–231, April-June 2012.
40. Fangqing Gu, Hai-lin Liu and Kay Chen Tan, “A Multiobjective Evolutionary Algorithm using Dynamic Weight Design
Method”, International Journal of Innovative Computing Information and Control, Vol. 8, No. 5B, pp. 3677–3688, May
2012.
41. Gilberto Reynoso-Meza, Javier Sanchis, Xavier Blasco and Juan M. Herrero, “Multiobjective evolutionary algorithms
for multivariable PI controller design”, Expert Systems with Applications, Vol. 39, No. 9, pp. 7895–7907, July 2012.
42. 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.
43. 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.
2733–2743, Part 2, July 2012.
44. Gustavo Olague and Leonardo Trujillo, “Interest point detection through multiobjective genetic programming”, Applied
Soft Computing, Vol. 12, No. 8, pp. 2566–2582, August 2012.
45. 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.
46. 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.
47. 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.
48. 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.
1891–1901, July 2012.
49. 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.
50. 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–
305, January-March 2012.
51. 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.
52. 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
River basins, South China”, Stochastic Environmental Research and Risk Assessment, Vol. 26, No. 4, pp. 497–507, May
2012.
53. 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.
54. 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
Engineering, Vol. 225, No. G11, pp. 1253–1261, November 2011.
55. I.G.P. Asto Buditjahjanto and Hajime Miyauchi, “An Intelligent Decision Support Based on a Subtractive Clustering and
Fuzzy Inference System for Multiobjective Optimization Problem in Serious Game”, International Journal of Information
Technology & Decision Making, Vol. 10, No. 5, pp. 793–810, September 2011.
56. 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.
C2, pp. 137–154, August 2011.
57. 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.
58. 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.
5

59. 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.
60. 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.
61. 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.
62. 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.
36–48, February 2012.
63. 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.
64. 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.
65. Yavuz Cengiz and Eray Konar, “Pareto-optimal synthesis of microwave amplifier to design the noise-constrained gain
value”, Microwave and Optical Technology Letters, Vol. 54, No. 4, pp. 1079–1084, April 2012.
66. T. Gomez, M. Hernandez, J. Molina, M.A. Leon, E. Aldana and R. Caballero, “A multiobjective model for forest
planning with adjacency constraints”, Annals of Operations Research, Vol. 190, No. 1, pp. 75–92, October 2011.
67. C.A. Garcia Montoya and S. Mendoza Toro, “Implementation of an evolutionary algorithm in planning investment in a
power distribution system”, Revista Ingeniería e Investigación, Vol. 31, Supplement: 2, pp. 118–124, 2011.
68. 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.
69. Shuo Xu, Ze Ji, Duc Truong Pham and Fan Yu, “Binary Bees Algorithm - bioinspiration from the foraging mechanism
of honeybees to optimize a multiobjective multidimensional assignment problem”, Engineering Optimization, Vol. 43,
No. 11, pp. 1141–1159, 2011.
70. Ben G. Small, Barry W. McColl, Richard Allmendinger, Jürgen Pahle, Gloria Lopez-Castejon, Nancy J. Rothwell, Joshua
Knowles, Pedro Mendes, David Brough and Doublas B. Kell, “Efficient discovery of anti-inflammatory small-molecule
combinations using evolutionary computing”, Nature Chemical Biology, Vol. 7, No. 12, pp. 902–908, December 2011.
71. Manojkumar Ramteke and Rajagopalan Srinivasan, “Novel genetic algorithm for short-term scheduling of sequence
dependent changeovers in multiproduct polymer plants”, Computers & Chemical Engineering, Vol. 35, No. 12, pp.
2945–2959, December 14, 2011.
72. Yun-Geun Lee, Bob Mckay, Kang-Il Kim, Dong-Kyun Kim and Nguyen Xuan Hoai, “Investigating vesicular selection A
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73. Guillermo Molina, Francisco Luna, Antonio J. Nebro and Enrique Alba, “An efficient local improvement operator for
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74. W.L. Wang, X.J. Yang, G.X. Xu and Y. Huang, “Multi-objective design optimization of the complete valve system
in an adjustable linear hydraulic damper”, Proceedings of the Institution of Mechanical Engineers Part C–Journal of
Mechanical Engineering Science, Vol. 225, No. C3, pp. 679–699, 2011.
75. Jose L. Bernal-Agustin and Rodolfo Dufo-Lopez, “Simulation and optimization of stand-alone hybrid renewable energy
systems”, Renewable & Sustainable Energy Reviews, Vol. 13, No. 8, pp. 2111–2118, October 2009.
76. Kwang Mong Sim and Bo An, “Evolving Best-Response Strategies for Market-Driven Agents Using Aggregative Fitness
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77. Md. Rafiul Hassan, Baikunth Nath, Michael Kirley and Joarde Kamruzzaman, “A hybrid of multiobjective Evolutionary
Algorithm and HMM-Fuzzy model for time series prediction”, Neurocomputing, Vol. 81, pp. 1–11, April 1, 2012.
78. Kent McClymont and Ed Keedwell, “Deductive Sort and Climbing Sort: New Methods for Non-Dominated Sorting”,
Evolutionary Computation, Vol. 20, No. 1, pp. 1–26, Spring 2012.
79. Teodor Marcu, Birgit Köppen-Seliger and Reinhard Stücher, “Design of fault detection for a hydraulic looper using
dynamic neural networks”, Control Engineering Practice, Vol. 16, No. 2, pp. 192–213, February 2008.
80. Christian Gagne and Marc Parizeau, “Coevolution of nearest neighbor classifiers”, International Journal of Pattern
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81. B.Y. Qu and P.N. Suganthan, “Constrained multi-objective optimization algorithm with an ensemble of constraint
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82. 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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83. Arnaud Liefooghe, Laetitia Jourdan and El-Ghazali Talbi, “A software framework based on a conceptual unified model
for evolutionary multiobjective optimization: ParadisEO-MOEO”, European Journal of Operational Research, Vol. 209,
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84. Massimiliano Manfren, Paola Caputo and Gaia Costa, “Paradigm shift in urban energy systems through distributed
generation: Methods and models”, Applied Energy, Vol. 88, No. 4, pp. 1032–1048, April 2011.
85. P.M. Reed and J.B. Kollat, “Save now, pay later? Multi-period many-objective groundwater monitoring design given
systematic model errors and uncertainty”, Advances in Water Resources, Vol. 35, pp. 55–68, January 2012.
86. C.W. Bong and M. Rajeswari, “Multiobjective clustering with metaheuristic: current trends and methods in image
segmentation”, IET Image Processing, Vol. 6, No. 1, pp. 1–10, February 2012.
87. Douglas A.G. Vieira, Ricardo H.C. Takahashi and Rodney R. Saldanha, “Multicriteria optimization with a multiobjective
golden section line search”, Mathematical Programming, Vol. 131, Nos. 1-2, pp. 131–161, February 2012.
88. H. Kordabadi and A. Jahanmiri, “A pseudo-dynamic optimization of a dual-stage methanol synthesis reactor in the face
of catalyst deactivation”, Chemical Engineering and Processing, Vol. 46, No. 12, pp. 1299–1309, December 2007.
89. David Daum and Nicolas Morel, “Assessing the saving potential of blind controller via multi-objective optimization”,
Building Simulation, Vol. 2, No. 3, pp. 175–185, September 2009.
90. Wei-Mei Chen, Hsien-Kuei Hwang and Tsung-Hsi Tsai, “Maxima-finding algorithms for multidimensional samples: A
two-phase approach”, Computational Geometry–Theory and Applications, Vol. 45, Nos. 1-2, pp. 33–53, January-
February 2012.
91. Lina Perelman, Avi Ostfeld and Elad Salomons, “Cross Entropy multiobjective optimization for water distribution
systems design”, Water Resources Research, Vol. 44, No. 9, Article Number: W09413, September 10, 2008.
92. Michael A. Trick and Hakan Yildiz, “Locally Optimized Crossover for the Traveling Umpire Problem”, European Journal
of Operational Research, Vol. 216, No. 2, pp. 286–292, January 16, 2012.
93. Diego P. Pinto-Roa, Benjamin Baran and Carlos A. Brizuela, “Routing and wavelength converter allocation in WDM
networks: a multi-objective evolutionary optimization approach”, Photonic Network Communications, Vol. 22, No. 1,
pp. 23–45, August 2011.
94. Marc Holze and Norbert Ritter, “System models for goal-driven self-management in autonomic databases”, Data &
Knowledge Engineering, Vol. 70, No. 8, pp. 685–701, August 2011.
95. Karsten Hentsch and Peter Köchel, “Job scheduling with forbidden setups and two objectives using genetic algorithms
and penalties”, Central European Journal of Operations Research, Vol. 19, No. 3, pp. 285–298, September 2011.
96. 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.
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97. 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.
98. 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.
99. 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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100. Mohammed Shalaby and Kazuhiro Saitou, “Design for Disassembly With High-Stiffness Heat-Reversible Locator-Snap
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101. B. Descamps, R. Filomeno Coelho, L. Ney and Ph. Bouillard, “Multicriteria optimization of lightweight bridge structures
with a constrained force density method”. Computers & Structures, Vol. 89, Nos. 3-4, pp. 277–284, February 2011.
102. 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.
103. 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.
83–103, 2011.
104. 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
Computer Applications, Vol. 34, No. 6, pp. 1794–1804, November 2011.
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105. 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.
106. Bruno Urli and Francois Terrien, “Project portfolio selection model, a realistic approach”, International Transactions in
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107. 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
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108. 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.
109. Minqiang Li, Dan Lin and Shouyang Wang, “Solving a type of biobjective bilevel programming problem using NSGA-
II”,k Computers & Mathematics with Applications, Vol. 59, No. 2, pp. 706–715, January 2010.
110. 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.
111. 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,
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112. 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.
113. 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.
114. Peter A. N. Bosman, “On Gradients and Hybrid Evolutionary Algorithms for Real-Valued Multiobjective Optimization”,
IEEE Transactions on Evolutionary Computation, Vol. 16, No. 1, pp. 51–69, February 2012.
115. 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–
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116. 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.
117. Eduardo Fernandez Gonzalez, Edy Lopez Cervantes, Jorge Navarro Castillo and Ines Vega Lopez, “Application of Multi-
Objective Metaheuristics to Public Portfolio Selection Through Multidimensional Modelling of Social Return”, Gestion
y Politica Publica, Vol. 20, No. 2, pp. 381–432, 2011.
118. 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.
119. 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.
120. 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.
121. Dan Zhang and Zhen Gao, “Hybrid head mechanism of the groundhog-like mine rescue robot”, Robotics and Computer-
Integrated Manufacturing, Vol. 27, No. 2, pp. 460–470, April 2011.
122. 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.
123. 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.
124. 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.
125. 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.
126. 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.
127. 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.
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128. 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.
129. Antonio L. Marquez, Raul Banos, Consolacion Gil, Maria G. Montoya, Francisco Manzano-Agugliaro and Francisco G.
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No. 6, pp. 649–656, November 2011.
130. 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.
131. 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.
132. 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.
133. 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.
134. 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.
135. Rajeev Kumar and Nilanjan Banerjee, “Multiobjective network topology design”, Applied Soft Computing, Vol. 11, No.
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136. 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
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137. 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.
138. 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.
139. 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.
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140. Ke Li, Sam Kwong, Jingjing Cao, Miqing Li, Jinhua Zheng and Ruimin Shen, “Achieving balance between proximity
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1, 2012.
141. 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.
142. 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.
143. 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.
144. Hans-Friedrich Köhn, “A review of multiobjective programming and its application in quantitative psychology”, Journal
of Mathematical Psychology, Vol. 55, No. 5, pp. 386–396, October 2011.
145. Sai Ho Yeung and Kim Fung, “Multiobjective Optimization”, IEEE Microwave Magazine, Vol. 12, No. 6, pp. 120–133,
October 2011.
146. 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.
147. 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,
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148. Karthik Sindhya, Sauli Ruuska, Tomi Haanpää 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.
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149. 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.
150. Emiliano Carreño Jara, “Long memory time series forecasting by using genetic programming”, Genetic Programming
and Evolvable Machines, Vol. 12, No. 4, pp. 429–456, December 2011.
151. 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.
152. Zbigniew Sekulski, “Multi-objective optimization of high speed vehicle-passenger catamaran by genetic algorithm Part
II Computational simulations”, Polish Maritime Research, Vol. 18, No. 3, pp. 3–30, 2011.
153. 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.
154. 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.
155. 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.
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156. Rodolfo Dufo-Lopez, Jose L. Bernal-Agustin, Jose M. Yusta-Loyo, Jose A. Dominguez-Navarro, Ignacio J. Ramirez-
Rosado, 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.
157. I. Alberto and P.M. Mateo, “A crossover operator that uses Pareto optimality in its definition”, TOP, Vol. 19, No. 1,
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158. 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.
159. 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.
160. 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.
161. 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.
162. 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.
163. 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.
164. Oscar Cordon, “A historical review of evolutionary learning methods for Mamdani-type fuzzy rule-based systems: Designing
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165. 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.
166. 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.
167. Reza Ghaemi, Nasir bin Sulaiman, Hamidah Ibrahim and Norwati Mustapha, “A review: accuracy optimization in
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168. Shafaq B. Chaudhry, Victor C. Hung, Ratan K. Guha and Kenneth O. Stanley, “Pareto-based evolutionary computational
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169. H. Safikhani, M.A. Akhavan-Behabadi, N. Nariman-Zadeh and M.J. Mahmood Abadi, “Modeling and multi-objective
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170. M.Sh. Levin and M.V. Petukhov, “Connection of Users with a Telecommunications Network: Multicriteria Assignment
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171. 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,
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172. Peter Vamplew, Richard Dazeley, Adam Berry, Rustam Issabekov and Evan Dekker, “Empirical evaluation methods for
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173. 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.
174. M.P. Cuellar, S. Capel-Cuevas, M.C. Pegalajar, I. de Orbe-Paya and L.F. Capitan-Vallvey, “Minimization of sensing
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175. B. Sankararao and Chang Kyoo Yoo, “Development of a Robust Multiobjective Simulated Annealing Algorithm for
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176. Pankaj Rajak, Ujjal Tewary, Sumitesh Das, Baidurya Bhattacharya and Nirupam Chakraborti, “Phases in Zn-coated
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177. Itishree Mohanty, Debashish Bhattacharjee and Shubhabrata Datta, “Designing cold rolled IF steel sheets with optimized
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178. Marianne Boix, Ludovic Montastruc, Luc Pibouleau, Catherine Azzaro-Pantel and Serge Domenech, “A multiobjective
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179. Zhanpeng Jin and Allen C. Cheng, “SubsetTrio: An Evolutionary, Geometric, and Statistical Benchmark Subsetting
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180. Chien-Ho Ko and Shu-Fan Wang, “Precast production scheduling using multi-objective genetic algorithms”, Expert
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181. Darrell F. Lochtefeld and Frank W. Ciarallo, “Helper-objective optimization strategies for the Job-Shop Scheduling
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182. Markus Hartikainen, Kaisa Miettinen and Margaret M. Wiecek, “Constructing a Pareto front approximation for decision
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183. Ata Allah Taleizadeh, Farnaz Barzinpour and Hui-Ming Wee, “Meta-heuristic algorithms for solving a fuzzy single-period
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184. 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.
185. Y.P. Ju and C.H. Zhang, “Multi-point and multi-objective optimization design method for industrial axial compressor
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186. A. Kundu and P.K. Dan, “The Scope of Genetic Algorithms in Dealing with Facility Layout Problems”, South African
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187. 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.
188. 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.
189. 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.
190. Yi Sun, Chaoyong Zhang, Liang Gao and Xiaojuan Wang, “Multi-objective optimization algorithms for flow shop
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191. 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.
192. 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.
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193. Satoshi Kitayama, Masao Arakawa and Koetsu Yamazaki, “Differential evolution as the global optimization technique
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194. 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.
195. 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,
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196. P. Rocca, G. Oliveri and A. Massa, “Differential Evolution as Applied to Electromagnetics”, IEEE Antennas and
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197. Yu Liang, Xiao-quan Cheng, Zheng-neng Li and Jin-wu Xiang, “Robust Multi-Objective Wing Design Optimization via
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198. Yann Cooren, Maurice Clerc and Patrick Siarry, “MO-TRIBES, an adaptive multiobjective particle swarm optimization
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199. 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.
200. 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.
201. 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.
202. 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.
203. 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.
204. A. Castelletti, A.V. Lotov and R. Soncini-Sessa, “Visualization-based multi-objective improvement of environmental
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205. 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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206. 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.
207. 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.
208. 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.
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209. 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.
210. 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.
211. 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.
212. 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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213. K. Sivakumar, C. Balamurugan and S. Ramabalan, “Simultaneous optimal selection of design and manufacturing tolerances
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214. Prithwish Chakraborty, Swagatam Das, Gourab Ghosh Roy and Ajith Abraham, “On convergence of the multi-objective
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215. K. Sivakumar, C. Balamurugan and S. Ramabalan, “Concurrent multi-objective tolerance allocation of mechanical
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216. 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.
217. Juan C. Vidal, Manuel Mucientes, Alberto Bugarín 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.
218. 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.
219. 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.
220. 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.
221. 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.
222. 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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223. 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.
224. 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.
225. 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.
226. F. Noori, M. Gorji, A. Kazemi and H. Nemati, “Thermodynamic optimization of ideal turbojet with afterburner engines
using non-dominated sorting genetic algorithm II”, Proceedings of the Institution of Mechanical Engineers Part G–Journal
of Aerospace Engineering, Vol. 224, No. G12, pp. 1285–1296, December 2010.
227. S.-Z. Zhao and P.N. Suganthan, “Two-lbests based multi-objective particle swarm optimizer”, Engineering Optimization,
Vol. 43, No. 1, pp. 1–17, January 2011.
228. H. Yapicioglu, H. Liu, A.E. Smith and G. Dozier, “Hybrid approach for Pareto front expansion in heuristics”, Journal
of the Operational Research Society, Vol. 62, No. 2, pp. 348–359, February 2011.
229. Clay Holdsworth, Minsun Kim, Jay Liao Mark H. Phillips, “A hierarchical evolutionary algorithm for multiobjective
optimization in IMRT”, Medical Physics, Vol. 37, No. 9, pp. 4986–4997, September 2010.
230. S.H. Yang, U. Natarajan, M. Sekar and S. Palani, “Prediction of surface roughness in turning operations by computer vision
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Technology, Vol. 51, Nos. 9–12, pp. 965–971, December 2010.
231. Isolina Alberto, Asuncion Beamonte, Pilar Gargallo, Pedro M. Mateo and Manuel Salvador, “Variable Selection in STAR
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232. Kyoung Seok Shin, Jong-Oh Park and Yeo Keun Kim, “Multi-objective FMS process planning with various flexibilities
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233. Kalyanmoy Deb, Kaisa Miettinen and Shamik Chaudhuri, “Toward an Estimation of Nadir Objective Vector Using a
Hybrid of Evolutionary and Local Search Approaches”, IEEE Transactions on Evolutionary Computation, Vol. 14, No.
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234. Christopher L. Simons, Ian C. Parmee and Rhys Gwynllyw, “Interactive, Evolutionary Search in Upstream Object-
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2010.
235. Aris Kornelakis, “Multiobjective Particle Swarm Optimization for the optimal design of photovoltaic grid-connected
systems”, Solar Energy, Vol. 84, No. 12, pp. 2022–2033, December 2010.
236. Ying Liu, Sudha Ram, Robert F. Lusch and Michael Brusco, “Multicriterion Market Segmentation: A New Model,
Implementation, and Evaluation”, Marketing Science, Vol. 29, No. 5, pp. 880–894, September-October 2010.
237. Dongdong Yang, Licheng Jiao, Maoguo Gong and Jie Feng, “Adaptive Ranks Clone and k-Nearest Neighbor List-Based
Immune Multi-Objective Optimization”, Computational Intelligence, Vol. 26, No. 4, pp. 359–385, November 2010.
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238. J. Branke, S. Greco, R. Slowinski and P. Zielniewicz, “Interactive evolutionary multiobjective optimization driven by
robust ordinal regression”, Bulletin of the Polish Academy of Sciences–Technical Series, Vol. 58, No. 3, pp. 347–358,
September 2010.
239. Mariano Frutos, Ana Carolina Olivera and Fernando Tohme, “A memetic algorithm based on a NSGAII scheme for the
flexible job-shop scheduling problem”, Annals of Operations Research, Vol. 181, No. 1, pp. 745–765, December 2010.
240. Isis Didier Lins and Enrique Lopez Droguett, “Redundancy allocation problems considering systems with imperfect repairs
using multi-objective genetic algorithms and discrete event simulation”, Simulation Modelling Practice and Theory,
Vol. 19, No. 1, pp. 362–381, January 2011.
241. Gift Dumedah, Aaron A. Berg, Mark Wineberg and Robert Collier, “Selecting Model Parameter Sets from a Trade-off
Surface Generated from the Non-Dominated Sorting Genetic Algorithm-II”, Water Resources Management, Vol. 24, No.
15, pp. 4469–4489, December 2010.
242. Massimiliano Kaucic, “Investment using evolutionary learning methods and technical rules”, European Journal of Operational
Research, Vol. 207, No. 3, pp. 1717–1727, December 16, 2010.
243. Javier Sanchis, Miguel A. Martinez, Xavier Blasco and Gilberto Reynoso-Meza, “Modelling preferences in multi-objective
engineering design”, Engineering Applications of Artificial Intelligence, Vol. 23, No. 8, pp. 1255–1264, December 2010.
244. Mohammad Hamdan, “On the Disruption-Level of Polynomial Mutation for Evolutionary Multi-Objective Optimisation
Algorithms”, Computing and Informatics, Vol. 29, No. 5, pp. 783–800, 2010.
245. N. Bel Hadj Ali and I.F.C. Smith, “Dynamic behavior and vibration control of a tensegrity structure”, International
Journal of Solids and Structures, Vol. 47, No. 9, pp. 1285–1296, May 1, 2010.
246. Lionel Gueguen and Berna Sayrac, “Efficient Spectrum Sensing With Dyadic Tree Partitioning”, IEEE Transactions on
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247. Konstantinos B. Baltzis and John N. Sahalos, “Suboptimal Rake Finger Allocation: Performance and Complexity
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248. F. Cosmi and B. Reggiani, “The optimization of parts within complex assemblies”, Proceedings of the Institution of
Mechanical Engineers Part C–Journal of Mechanical Engineering Science, Vol. 224, No. C4, pp. 969–979, 2010.
249. Maurizio Galetto and Barbara Pralio, “Optimal sensor positioning for large scale metrology applications”, Precision
Engineering—Journal of the International Societies for Precision Engineering and Nanotechnology, Vol. 34, No. 3, pp.
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250. Nenzi Wang and Kuo-Chiang Cha, “Multi-objective optimization of air bearings using hypercube-dividing method”,
Tribology International, Vol. 43, No. 9, pp. 1631–1638, September 2010.
251. Anselmo Ramalho Pitombeira Neto and Eduardo Vila Goncalves Filho, “A simulation-based evolutionary multiobjective
approach to manufacturing cell formation”, Computers & Industrial Engineering, Vol. 59, No. 1, pp. 64–74, August
2010.
252. Konstantinos Delibasis, Pantelis A. Asvestas and George K. Matsopoulos, “Multimodal genetic algorithms-based algorithm
for automatic point correspondence”, Pattern Recognition, Vol. 43, No. 12, pp. 4011–4027, December 2010.
253. A. Deihimi and H. Javaheri, “A Fuzzy Multi-Objective Multi-Case Genetic-Based Optimization for Allocation of FACTS
Devices to Improve System Static Security, Power Loss and Transmission Line Voltage Profiles”, International Review
of Electrical Engineering–IREE, Vol. 5, No. 4, pp. 1616–1626, Part B, July-August 2010.
254. Manuel Chica, Oscar Cordon, Sergio Damas and Joaquin Bautista, “Including different kinds of preferences in a multiobjective
ant algorithm for time and space assembly line balancing on different Nissan scenarios”, Expert Systems with
Applications, Vol. 38, No. 1, pp. 709–720, January 2011.
255. E. Herrera-Viedma and A.G. Lopez-Herrera, “A Review on Information Accessing Systems Based on Fuzzy Linguistic
Modelling”, International Journal of Computational Intelligence Systems, Vol. 3, No. 4, pp. 420–437, October 2010.
256. Cristobal Jose Carmona, Pedro Gonzalez, Maria Jose del Jesus and Francisco Herrera, “NMEEF-SD: Non-dominated
Multiobjective Evolutionary Algorithm for Extracting Fuzzy Rules in Subgroup Discovery”, IEEE Transactions on Fuzzy
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257. Ranjan Bhattacharya and Susmita Bandyopadhyay, “Solving conflicting bi-objective facility location problem by NSGA
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258. Manuel E. Fernandez Garcia, Enrique A. Marin and Raquel Quiroga Garcia, “Improving return using risk-return adjustment
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259. Celine Badufle, Christophe Blondel, Thierry Druot, Christian Bes, Jean-Baptiste Hiriart-Urruty, “A heuristic-based
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260. Ibrahim Karahan and Murat Köksalan, “A Territory Defining Multiobjective Evolutionary Algorithms and Preference
Incorporation”, IEEE Transactions on Evolutionary Computation, Vol. 14, No. 4, pp. 636–664, August 2010.
261. Lily Rachmawati and Dipti Srinivasan, “Incorporating the Notion of Relative Importance of Objectives in Evolutionary
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262. Kalyanmoy Deb, Amkur Sinha, Pekka J. Korhonen and Jyrki Wallenius, “An Interactive Evolutionary Multiobjective
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263. Murat Köksalan and Ibrahim Karahan, “An Interactive Territory Defining Evolutionary Algorithm: iTDEA”, IEEE
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264. Guilherme P. Coelho, Ana Estela A. da Silva and Fernando J. Von Zuben, “An immune-inspired multi-objective approach
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2010.
265. Huidong Jin and Man-Leung Wong, “Adaptive, convergent, and diversified archiving strategy for multiobjective evolutionary
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266. A. Agarwal, U. Tewary, F. Pettersson, S. Das, H. Saxen H and N. Chakraborti, “Analysing blast furnace data using
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267. J.C. Fernandez, C. Hervas, F.J. Martinez-Estudillo and P.A. Gutierrez, “Memetic Pareto Evolutionary Artificial Neural
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268. Krzysztof Kurowski, Ariel Oleksiak and Jan Weglarz, “Multicriteria, multi-user scheduling in grids with advance reservation”,
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269. F. Günes and F. Tokan, “Pareto Optimal Synthesis of the Linear Array Geometry for Minimum Side lobe Level and
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270. Sultan Noman Qasem and Siti Mariyam Shamsuddin, “Radial basis function network based on time variant multiobjective
particle swarm optimization for medical diseases diagnosis”, Applied Soft Computing, Vol. 11, No. 1, pp.
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271. Marco Cococcioni, Beatrice Lazzerini and Francesco Marcelloni, “On reducing computational overhead in multi-objective
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272. Gideon Avigad and Amiram Moshaiov, “Simultaneous concept-based evolutionary multi-objective optimization”, Applied
Soft Computing, Vol. 11, No. 1, pp. 193–207, January 2011.
273. Piotr Wozniak, “Preferences in multi-objective evolutionary optimisation of electric motor speed control with hardware
in the loop”, Applied Soft Computing, Vol. 11, No. 1, pp. 49–55, January 2011.
274. Coromoto Leon, Gara Miranda and Carlos Segura, “METCO: A Parallel Plugin-Based Framework for Multi-Objective
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275. M.N. Neema and A. Ohgai, “Multi-objective location modeling of urban parks and open spaces: Continuous optimization”,
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276. N. Chakraborti, R. Sreevathsan, R. Jayakanth and B. Bhattacharya, “Tailor-made material design: An evolutionary
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277. Hassan K. Abdulrahim and Fuad N. Alasfour, “Multi-Objective Optimisation of hybrid MSF-RO desalination system
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278. Maria Jose Gacto, Rafael Alcala and Francisco Herrera, “Integration of an Index to Preserve the Semantic Interpretability
in the Multiobjective Evolutionary Rule Selection and Tuning of Linguistic Fuzzy Systems”, IEEE Transactions on Fuzzy
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279. B. Cobacho, R. Caballero, M. Gonzalez and J. Molina, “Planning federal public investment in Mexico using multiobjective
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280. Tomas Petkus, Ernestas Filatovas and Olga Kurasova, “Investigation of Human Factors while Solving Multiple Criteria
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281. S.H. Yang and U. Natarajan, “Multi-objective optimization of cutting parameters in turning process using differential
evolution and non-dominated sorting genetic algorithm-II approaches”, International Journal of Advanced Manufacturing
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282. Jiaquan Gao, Lei Fang and Jun Wang, “A weight-based multiobjective immune algorithm: WBMOIA”, Engineering
Optimization, Vol. 42, No. 8, pp. 719–745, 2010.
283. Manuel Chica, Oscar Cordon, Sergio Damas and Joaquin Bautista, “Multiobjective constructive heuristics for the 1/3
variant of the time and space assembly line balancing problem: ACO and random greedy search”, Information Sciences,
Vol. 180, No. 18, pp. 3465–3487, September 15, 2010.
284. F. Günes and F. Tokan, “Pareto Optimal Synthesis of the Linear Array Geometry for Minimum Side lobe Level and
Null Control During Beam Scanning”, International Journal of RF and Microwave Computer-Aided Engineering, Vol.
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285. Yu Liang, XiaoQuan Cheng, ZhengNeng Li and JinWu Xiang, “Effect of cavity flame holder configuration on combustion
flow field performance of integrated hypersonic vehicle”, Science China–Technological Sciences, Vol. 53, No. 10, pp.
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286. Shuo Xu, Ze Ji, Duc Troung Pham and Fan Yu, “Bio-Inspired Binary Bees Algorithm for a Two-Level Distribution
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287. John Nicklow, Patrick Reed, Dragan Savic, Tibebe Dessalegne, Laura Harrell, Amy Chan-Hilton, Mohammad Karamouz,
Barbara Minsker, Avi Ostfeld, Abhishek Singh and Emily Zechman, “State of the Art for Genetic Algorithms and Beyond
in Water Resources Planning and Management”, Journal of Water Resources Planning and Management–ASCE, Vol.
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288. Milica Selmic, Dusan Teodorovic and Katarina Vukadinovic, “Locating inspection facilities in traffic networks: an
artificial intelligence approach”, Transportation Planning and Technology, Vol. 33, No. 6, pp. 481–493, 2010.
289. C. Fernandes, A.J. Pontes, J.C. Viana and A. Gaspar-Cunha, “Using Multiobjective Evolutionary Algorithms in the
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290. T. Aittokoski and K. Miettinen, “Efficient evolutionary approach to approximate the Pareto-optimal set in multiobjective
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291. Francisco Luna, Juan J. Durillo, Antonio J. Nebro and Enrique Alba, “Evolutionary algorithms for solving the automatic
cell planning problem: a survey”, Engineering Optimization, Vol. 42, No. 7, pp. 671–690, 2010.
292. Dudy Lim, Yaochu Jin, Yew-Soon Ong and Bernhard Sendhoff, “Generalizing Surrogate-Assisted Evolutionary Computation”,
IEEE Transactions on Evolutionary Computation, Vol. 14, No. 3, pp. 329–355, June 2010.
293. Santosh Tiwari, Georges Fadel and Peter Fenyes, “A Fast and Efficient Compact Packing Algorithm for SAE and ISO
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294. M.T. Yazdani Sabouni, F. Jolai and A. Mansouri, “Heuristics for minimizing total completion time and maximum
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295. Abdelaziz Hammache, Marzouk Benali and Francois Aube, “Multi-objective self-adaptive algorithm for highly constrained
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296. Jiaquan Gao, Lei Fang and Jun Wang, “A weight-based multiobjective immune algorithm: WBMOIA”, Engineering
Optimization, Vol. 42, No. 8, pp. 719–745, 2010.
297. Shang-Jeng Tsai, Tsung-Ying Sun, Chan-Cheng Liu, Sheng-Ta Hsieh, Wun-Ci Wu and Shih-Yuan Chiu, “An improved
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298. K. Salmalian, N. Nariman-Zadeh, H. Gharababei, H. Haftchenari and A. Varvani-Farahani, “Multi-objective evolutionary
optimization of polynomial neural networks for fatigue life modelling and prediction of unidirectional carbon-fibrereinforced
plastics composites”, Proceedings of the Institution of Mechanical Engineers Part L–Journal of Materials-
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299. N. Nariman-Zadeh, M. Salehpour, A. Jamali and E. Haghgoo, “Pareto optimization of a five-degree of freedom vehicle
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Artificial Intelligence, Vol. 23, No. 4, pp. 543–551, June 2010.
300. Hemant Kumar Singh, Tapabrata Ray and Warren Smith, “C-PSA: Constrained Pareto simulated annealing for constrained
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301. Rocio L. Cecchini, Carlos M. Lorenzetti, Ana G. Maguitman and Nelida B. Brignole, “Multiobjective Evolutionary
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302. Juan Carlos Fernandez Caballero, Francisco Jose Martinez, Cesar Hervas and Pedro Antonio Gutierrez, “Sensitivity
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303. Gideon Avigad, Erella Eisenstadt and Alexander Goldvard, “Pareto layer: Its formulation and search by way of evolutionary
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404. Feili Yu, Fang Tu, Krishna R. Pattipati, “Integration of a holonic organizational control architecture and multiobjective
evolutionary algorithm for flexible distributed scheduling”, IEEE Transactions on Systems, Man, and Cybernetics Part
A–Systems and Humans, Vol. 38, No. 5, pp. 1001–1017, September 2008.
405. Christian Gagne, Julie Beaulieu, Marc Parizeau and Simon Thibault, “Human-competitive lens system design with
evolution strategies”, Applied Soft Computing, Vol. 8, No. 4, pp. 1439–1452, September 2008.
406. Leandro dos Santos Coelho and Piergiorgio Alotto, “Multiobjective electromagnetic optimization based on a nondominated
sorting genetic approach with a chaotic crossover operator”, IEEE Transactions on Magnetics, Vol. 44, No. 6,
pp. 1078–1081, June 2008.
407. Laetitia Jourdan, Oliver Schuetze, Thomas Legrand, El-Ghazali Talbi and Jean Luc Wojkiewicz, “An Analysis of the Effect
of Multiple Layers in the Multi-Objective Design of Conducting Polymer Composites”, Materials and Manufacturing
Processes, Vol. 24, No. 3, pp. 350–357, 2009.
408. Oliver Schuetze, Laetitia Jourdan, Thomas Legrand, El-Ghazali Talbi and Jean-Luc Wojkiewicz, “New analysis of
the optimization of electromagnetic shielding properties using conducting polymers and a multi-objective approach”,
Polymers for Advanced Technologies, Vol. 19, No. 7, pp. 762–769, July 2008.
409. Frank Pettersson, Arijit Biswas, Prodip Kumar Sen, Henrik Saxén and Nirupam Chakraborti, “Analyzing Leaching Data
for Low-Grade Manganese Ore Using Neural Nets and Multiobjective Genetic Algorithms”, Materials and Manufacturing
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410. Akash Agarwal, Frank Pettersson, Arunima Singh, Chang Sun Kong, Henrik Saxén, Krishna Rajan, Shuichi Iwata and
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Neural Nets, and Multiobjective Genetic Algorithms”, Materials and Manufacturing Processes, Vol. 24, No. 3, pp.
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411. Oliver Schütze, Massimiliano Vasile, Oliver Junge, Michael Dellnitz and Dario Izzo, “Designing optimal low-thrust
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412. Jesús García Herrero, Antonio Berlanga and José Manuel Molina López, “Effective Evolutionary Algorithms for Many-
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413. Lam T. Bui, Hussein A. Abbass and Daryl Essam, “Local models—an approach to distributed multi-objective optimization”,
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414. Rocío C. Romero-Zaliz, Cristina Rubio-Escudero, J. Perren Cobb, Francisco Herrera, Óscar Cordón and Igor Zwir, “A
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415. R. Brits, A.P. Engelbrecht and F. van den Bergh, “Locating multiple optima using particle swarm optimization”, Applied
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417. J.M. Nobrega, O.S. Carneiro, A. Gaspar-Cunha and N.D. Goncalves, “Design of calibrators for profile extrusion -
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418. Shao Yong Zheng, Sai Ho Yeung, Wing Shing Chan, Kim Fung Man, Shu Hung Leung and Quan Xue, “Dual-band
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419. S.Y.S. Leung, W.K. Wong and P.Y. Mok, “Multiple-objective genetic optimization of the spatial design for packing and
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420. Xiufen Zou, Yu Chen, Minzhong Liu and Lishan Kang, “A New Evolutionary Algorithm for Solving Many-Objective
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421. N. Chakraborti, A. Shekhar, A. Singhal, S. Chakraborty, S. Chowdhury and R. Sripriya, “Fluid flow in hydrocyclones
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422. Min Zhang, Wenjian Luo and Xufa Wang, “Differential evolution with dynamic stochastic selection for constrained
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423. Elizabeth F. Wanner, Frederico G. Guimarães, Ricardo H.C. Takahashi and Peter J. Fleming, “Local Search with
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424. Antonio J. Nebro, Francisco Luna, Enrique Alba, Bernabé Dorronsoro, Juan J. Durillo and Andreas Beham, “AbYSS:
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425. Frederic Ros, Serge Guillaume, Marco Pintore and Jacques R. Chretien, “Hybrid genetic algorithm for dual selection”,
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426. Maoguo Gong, Licheng Jiao, Haifeng Du and Liefeng Bo, “Multiobjective immune algorithm with nondominated
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427. Mohammed Khabzaoui, Clarisse Dhaenens and El-Ghazali Talbi, “Combining evolutionary algorithms and exact approaches
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428. J. Reca, J. Martinez, R. Banos and C. Gil, “Optimal design of gravity-fed looped water distribution networks considering
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429. Sanghamitra Bandyopadhyay, Sriparna Saha, Ujjwal Maulik and Kalyanmoy Deb, “A Simulated Annealing-Based Multiobjective
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430. N. Chakraborti, B. Siva Kumar, V. Satish Babu, S. Moitra and A. Mukhopadhyay, “A new multi-objective genetic
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431. Hamidreza Eskandari and Christopher D. Geiger, “A fast Pareto genetic algorithm approach for solving expensive
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432. Philipp Limbourg and Hans-Dieter Kochs, “Multi-objective optimization of generalized reliability design problems using
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433. Jun Guo, Yi Wang, Kit-Sang Tang, Sammy Chan, Eric W.M. Wong, Peter Taylor and Moshe Zukerman, “Evolutionary
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434. Sai-Ho Yeung, Hoi-Kuen Ng and Kim-Fung Man, “Multi-criteria design methodology of a dielectric resonator antenna
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435. David S. Robin, Wan Weishi Wan, Fernando Sannibale and Victor P. Suller, “Global analysis of all linear stable settings
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436. Nicolas Jozefowiez, Frederic Semet and El-Ghazali Talbi, “Multi-objective vehicle routing problems”, European Journal
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437. Miguel Delgado, Manuel P. Cuellar and Maria Carmen Pegalajar, “Multiobjective hybrid optimization and training of
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438. Xingdong Zhang and Marc P. Armstrong, “Genetic algorithms and the corridor location problem: multiple objectives
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439. Wasim Raza and Kwang-Yong Kim, “Multiobjective optimization of a wire-wrapped LMR fuel assembly”, Nuclear
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440. J.M. Herrero, X. Blasco, M. Martinez, C. Ramos and J. Sanchis, “Robust identification of non-linear greenhouse model
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442. Fabian Duddeck, “Multidisciplinary optimization of car bodies”, Structural and Multidisciplinary Optimization, Vol. 35,
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443. Ricardo Perera and Antonio Ruiz, “A multistage FE updating procedure for damage identification in large-scale structures
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444. Gio J. Kao and Sheldon H. Jacobson, “Finding preferred subsets of Pareto optimal solutions”, Computational Optimization
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445. A. I. Olcer, “A hybrid approach for multi-objective combinatorial optimisation problems in ship design and shipping”,
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446. Hisao Ishibuchi, Kaname Narukawa, Noritaka Tsukamoto and Yusuke Nojima, “An empirical study on similarity-based
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447. Annette Muetze, “A neglected stepchild”, IEEE Industry Applications Magazine, Vol. 14, No. 2, pp. 14–22, March-April
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448. N. Amanifard, N. Nariman-Zadeh, M. Borji, A. Khalkhali and A. Habibdoust, “Modelling and Pareto optimization of
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449. N. Nariman-zadeh, A. Jamali and A. Hajiloo, “Frequency-based reliability Pareto optimum design of proportionalintegral-derivative
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450. Shubhabrata Datta, Frank Pettersson, Subhas Ganguly, Henrik Saxen and Nirupam Chakraborti, “Identification of
factors governing mechanical properties of TRIP-aided steel using genetic algorithms and neural networks”, Materials
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451. Bin Qian, Ling Wang, De-Xian Huang and Xiong Wang, “Scheduling multi-objective job shops using a memetic algorithm
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452. O. Giustolisi, A. Doglioni, D.A. Savic and F. di Pierro, “An evolutionary multiobjective strategy for the effective
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453. Eduardo Fernandez, Nora Cancela and Rafael Olmedo, “Deriving a final ranking from fuzzy preferences: An approach
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454. Javier Sanchis, Miguel A. Martinez and Xavier Blasco, “Integrated multiobjective optimization and a priori preferences
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455. J. Sanchis, M. Martinez and X. Blasco, “Multi-objective engineering design using preferences”, Engineering Optimization,
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456. 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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457. Zbigniew Michalewicz and Matthew Michalewicz, “Machine intelligence, adaptive business intelligence, and natural
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458. F. Pettersson, N. Chakraborti and S.B. Singh, “Neural Networks Analysis of Steel Plate Processing Augmented by
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459. Qingfu Zhang, Aimin Zhou and Yaochu Jin, “RM-MEDA: A Regularity Model-Based Multiobjective Estimation of
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460. A. Gaspar-Cunha and J.A. Covas, “Robustness in multi-objective optimization using evolutionary algorithms”, Computational
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461. Genci Capi, “Multiobjective evolution of neural controllers and task complexity”, IEEE Transactions on Robotics, Vol.
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462. J.M. Herrero, X. Blasco, M. Martinez, C. Ramos and J. Sanchis, “Non-linear robust identification of a greenhouse model
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463. Ang Yang, Hussein A. Abbass and Ruhul Sarker, “Characterizing warfare in red teaming”, IEEE Transactions on
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464. Julian Molina, Manuel Laguna, Rafael Marti and Rafael Caballero, “SSPMO: A scatter tabu search procedure for
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466. Qingfu Zhang and Hui Li, “MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition”, IEEE
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467. Sebastián Ventura, Cristóbal Romero, Amelia Zafra, José A. Delgado and César Hervás, “JCLEC: a Java framework for
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468. Joshua B. Kollat and Patrick Reed, “A framework for visually interactive decision-making and design using evolutionary
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469. Marco A. Panduro, Carlos A. Brizuela and David H. Covarrubias, “Design of electronically steerable linear arrays with
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470. Kay-Soon Low and Tze-Shyan Wong, “A multiobjective genetic algorithm for optimizing the performance of hard disk
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471. Arlene G. Smithson, Karim Hamza and Kazuhiro Saitou, “Design for existing lines: Part and process plan optimization
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472. DaeEun Kim and Jaehong Park, “Application of adaptive control to the fluctuation of engine speed at idle”, Information
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473. A.F. Gomez-Skarmeta, F. Jimenez and G. Sanchez, “Improving interpretability in approximative fuzzy models via
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474. Sarbajit Pal, Pankaj Ganguly and P.K. Biswas, “Cubic Bezier approximation of a digitized curve”, Pattern Recognition,
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475. Maria Jose del Jesus, Pedro Gonzalez, Francisco Herrera and Mikel Mesonero, “Evolutionary fuzzy rule induction process
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476. Luciano Sanchez and Ines Couso, “Advocating the use of imprecisely observed data in genetic fuzzy systems”, IEEE
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478. S. Dehuri, S. Patnaik, A. Ghosh and R. Mall, “Application of elitist multi-objective genetic algorithm for classification
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479. Ricardo Perera, Antonio Ruiz and Carlos Manzano, “An evolutionary multiobjective framework for structural damage
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480. M. Ye and G. Zhouz, “A local genetic approach to multi-objective, facility layout problems with fixed aisles”, International
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481. Guangtao Fu, David Butler and Soon-Thiam Khu, “Multiple objective optimal control of integrated urban wastewater
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482. Yuren Zhou and Jun He, “Convergence analysis of a self-adaptive multi-objective evolutionary algorithm based on grids”,
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483. David Midgley, Robert Marks and Dinesh Kunchamwar, “Building and assurance of agent-based models: An example
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484. Shubhabrata Datta, Frank Pettersson, Subhas Ganguly, Henrik Saxén and Niruopam Chakraborti, “Designing High
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487. Kumara Sastry, D.D. Johnson, Alexis L. Thompson, David E. Goldberg, Todd J. Martinez, Jeff Leiding and Jane
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488. Henrik Saxén, Frank Pettersson and Kiran Gunturu, “Evolving Nonlinear Time-Series Models of the Hot Metal Silicon
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489. Kaisa Miettinen, “Using Interactive Multiobjective Optimization in Continuous Casting of Steel”, Materials and Manufacturing
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490. S. Ganguly, S. Datta and N. Chakraborti, “Genetic algorithms in optimization of strength and ductility of low-carbon
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491. Eleni Aggelogiannaki and Haralarnbos Sarimveis, “Simulated annealing algorithm for prioritized multiobjective optimizationimplementation
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492. Christian Gagne and Marc Parizeau, “Genetic engineering of hierarchical fuzzy regional representations for handwritten
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493. Don Jyh-Fu Jeng, Ikno Kim and Junzo Watada, “Bio-soft computing with fixed-length DNA to a group control optimization
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494. Antonio Pinto, Daniele Peri and Emilio F. Campana, “Multiobjective optimization of a containership using deterministic
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495. Jing Liu, Weicai Zhong and Licheng Hao, “An organizational evolutionary algorithm for numerical optimization”, IEEE
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497. Joern Mehnen, Thomas Michelitsch, Christian Lasarczyk and Thomas Bartz-Beielstein, “Multi-objective evolutionary
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498. Pascal Côté, Lael Parrott and Robert Sabourin, “Multi-objective optimization of an ecological assembly model”, Ecological
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499. Maria Joao Alves and Marla Almeida, “MOTGA: A multiobjective Tchebycheff based genetic algorithm for the multidimensional
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500. Mario Köppen, Katrin Franke and Raul Vicente-Garcia, “Tiny GAs for image processing applications”, IEEE Computational
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501. G. Li, M. Li, S. Azarm, J. Rambo and Y. Joshi, “Optimizing thermal design of data center cabinets with a new
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505. Ivan Blecic, Arnaldo Cecchini and Giuseppe A. Trunfio, “A decision support tool coupling a causal model and a multiobjective
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506. J.W. Large, D.F. Jones and M. Tamiz, “Hyper-spherical inversion transformations in multi-objective evolutionary optimization”,
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508. M.R. Gholamian, S.M.T. Fatemi Ghomi and M. Ghazanfari, “A hybrid system for multiobjective problems - A case
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510. Carlos Gomes da Silva, José Figueira and João Clímaco, “Integrating partial optimization with scatter search for solving
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512. C. Gil, A. Marquez, R. Baños, M.G. Montoya and J. Gomez, “A hybrid method for solving multi-objective global
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513. Ningchuan Xiao, David A. Bennett and Marc P. Armstrong, “Interactive evolutionary approaches to multiobjective
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May 2007.
514. Julia Handl, Douglas B. Kell and Joshua Knowles, “Multiobjective optimization in bioinformatics and computational
biology”, IEEE-ACM Transactions on Computational Biology and Bioinformatics, Vol. 4, No. 2, pp. 279–292, April-
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515. David I. Broadhurst and Douglas B. Kell, “Statistical strategies for avoiding false discoveries in metabolomics and related
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516. A.J. Rivera, I. Rojas, J. Ortega and M.J. del Jesus, “A new hybrid methodology for cooperative-coevolutionary optimization
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518. Andres L. Medaglia, Samuel B. Graves and Jeffrey L. Ringuest, “A multiobjective evolutionary approach for linearly
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704. S. Ganguly, S. Datta, P.P. Chattopadhyay and N. Chakraborti, “Designing the Multiphase Microstructure of Steel for
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719. A.F. Carazo, Trinidad Gomez, Julian Molina, Alfredo G. Hernandez-Diaz, Flor M. Guerrero and Rafael Caballero,
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726. J.E. Mendoza, L.A. Villaleiva, M.A. Castro and E.A. Lopez, “Multi-objective Evolutionary Algorithms for Decision-
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732. M.H. Khoshgoftar Manesh and Majid Amidpour, “Multi-objective thermoeconomic optimization of coupling MSF desalination
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733. 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.
734. 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.
735. 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.
736. 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.
737. 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.
738. 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.
739. 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.
740. 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.
741. 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.
742. 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.
743. Nicola Beume, Boris Naujoks and Guenter Rudolph, “SMS-EMOA - Effective Evolutionary Multiobjective Optimization”,
AT-Automatisierungstechnik, Vol. 56, No. 7, pp. 357–364, 2008.
744. 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.
745. 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.
746. Ioannis C. Kampolis and Kyriakos C. Giannakoglou, “Distributed evolutionary algorithms with hierarchical evaluation”,
Engineering Optimization, Vol. 41, No. 11, pp. 1037–1049, November 2009.
747. Patrick M. Reed, Joshua B. Kollat, Matthew P. Ferringer and Timothy G. Thompson, “Parallel Evolutionary Multi-
Objective Optimization on Large, Heterogeneous Clusters: An Applications Perspective”, Journal of Aerospace Computing
Information and Communication, Vol. 5, No. 11, pp. 460–478, 2008.
748. 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,
Vol. 59, No. 5, pp. 681–688, October 2006.
37

749. 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.
750. 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.
751. 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.
752. 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.
753. Gisele L. Pappa and Alex A. Freitas, “Evolving rule induction algorithms with multi-objective grammar-based genetic
programming”, Knowledge and Information Systems, Vol. 19, No. 3, pp. 283–309, June 2009.
754. 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–
1082, October 2009.
755. 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,
Vol. 14, No. 4, pp. 231–245, December 2009.
756. 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.
757. 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.
758. Parames Chutima and Penpak Pinkoompee, “Multi-objective sequencing problems of mixed-model assembly systems
using memetic algorithms”, Scienceasia, Vol. 35, No. 3, pp. 295–305, September 2009.
759. 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.
760. 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.
761. 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–
1082, October 2009.
762. 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.
763. 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.
764. 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.
765. Yang Zhang and Peter Rockett, “A Comparison of three evolutionary strategies for multiobjective genetic programming”,
Artificial Intelligence Review, Vol. 27, Nos. 2–3, pp. 149–163, March 2007.
766. 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.
767. 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.
768. 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.
769. Hai-Lin Liu, Yuping Wang and Yiu-Ming Cheung, “A Multi-Objective Evolutionary Algorithm using Min-Max Strategy
and Sphere Coordinate Transformation”, Intelligent Automation and Soft Computing, Vol. 15, No. 3, pp. 361–384,
2009.
770. Hussein A. Abbass, Sameer Alam and Axel Bender, “MEBRA: Multiobjective Evolutionary-Based Risk Assessment”,
IEEE Computational Intelligence Magazine, Vol. 4, No. 3, pp. 29–36, August 2009.
38

771. 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.
772. 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.
773. 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.
774. 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.
775. 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.
776. 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.
777. 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.
778. 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.
779. 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.
780. Ata Allah Taleizadeh, Seyed Taghi Akhavan Niaki and Mir-Bahador Aryanezhad, “A hybrid method of Pareto, TOP-
SIS 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.
781. 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.
782. 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.
783. 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.
784. 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.
785. 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.
786. 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.
787. 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.
788. 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.
789. 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.
790. 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.
791. 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.
39

792. Benjamin Torben-Nielsen and Klaus M. Stiefel, “Systematic mapping between dendritic function and structure”, Network-
Computation in Neural Systems, Vol. 20, No. 2, pp. 59–105, 2009.
793. 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.
794. 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.
795. 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.
796. Ricardo Brunelli and Christian von Lücken, “Optimal Crop Selection Using Multiobjective Evolutionary Algorithms”,
AI Magazine, Vol. 30, No. 2, pp. 96–105, Summer 2009.
797. 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.
798. 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.
799. 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.
800. 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.
801. 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.
802. 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.
803. 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.
804. 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.
805. 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.
806. 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.
807. 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.
808. Annette Chmielewski, Boris Naujoks, Michael Janas and Uwe Clausen, “Optimizing the Door Assignment in LTL-
Terminals”, Transportation Science, Vol. 43, No. 2, pp. 198–210, May 2009.
809. 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.
810. 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.
811. 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.
812. 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.
40

Capítulos de Libros
• 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.
• Efrén Mezura-Montes, Lucía Muñoz-Dávila 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.
1. 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.
• 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 978-3-642-04225-
6.
1. 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.
1. 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.
2. Zbigniew Sekulski, “Multi-objective optimization of high speed vehicle-passenger catamaran by genetic algorithm Part
II Computational simulations”, Polish Maritime Research, Vol. 18, No. 3, pp. 3–30, 2011.
• El-Ghazali Talbi, Sanaz Mostaghim, Tatsuya Okabe, Hisao Ishibuchi, Günter Rudolph and Carlos A. Coello
Coello, “Parallel Approaches for Multi-objective Optimization”, in Jürgen Branke, Kalyanmoy Deb, Kaisa
Miettinen and Roman Slowinski (editors), Multiobjective Optimization. Interactive and Evolutionary Approaches,
pp. 349–372, Springer, Lecture Notes in Computer Science Vol. 5252, Berlin, Germany, 2008.
1. 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.
2. 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.
3. 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,
pp. 464–479, 2009.
• Antonio López Jaimes, Luis Vicente Santana Quintero and Carlos A. Coello Coello, “Ranking Methods
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.
1. 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.
2. 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.
• 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),
Evolutionary Computation in Dynamic and Uncertain Environments, pp. 269–296, Springer, 2007, ISBN
978-3-540-49772-1.
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1. Carlos Cruz, Juan R. Gonzalez and David A. Pelta, “Optimization in dynamic environments: a survey on problems,
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.
1. 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.
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.
• Efrén Mezura-Montes, Margarita Reyes-Sierra and Carlos A. Coello Coello, “Multi-Objective Optimization
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 978-3-540-
68827-3.
1. Feng Qian, Bing Xu, Rongbin Qi and Huaglory Tianfield, “Self-adaptive differential evolution algorithm with alphaconstrained-domination
principle for constrained multi-objective optimization”, Soft Computing, Vol. 16, No. 8, pp.
1353–1372, August 2012.
2. Chunhua Peng, Huijuan Sun, Jianfeng Guo and Gang Liu, “Multi-objective optimal strategy for generating and bidding
in the power market”, Energy Conversion and Management, Vol. 57, pp. 13–22, May 2012.
3. 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.
4. Ferrante Neri and Ville Tirronen, “Recent advances in differential evolution: a survey and experimental analysis”,
Artificial Intelligence Review, Vol. 33, Nos. 1-2, pp. 61–106, February 2010.
• Luis V. Santana-Quintero, Noel Ramírez-Santiago and Carlos A. Coello Coello, “Towards a More Efficient
Multi-Objective Particle Swarm Optimizer”, in Lam Thu Bui and Sameer Alam (editors), Multi-Objective
Optimization in Computational Intelligence: Theory and Practice, Chapter IV, pp. 76–105, Information
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1. 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.
• Antonio López Jaimes and Carlos A. Coello Coello, “Multi-Objective Evolutionary Algorithms: A Review
of the State-of-the-Art and some of their Applications in Chemical Engineering”, in Rangaiah Gade Pandu
(editor), Multi-Objective Optimization Techniques and Applications in Chemical Engineering, Chapter 3, pp.
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Recognition Letters, Vol. 31, No. 13, pp. 1781–1794, October 1, 2010.
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literature review”, Expert Systems with Applications, Vol. 39, No. 14, pp. 11685–11698, October 15, 2012.
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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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and What Remains to be Done”, in Gary Y. Yen and David B. Fogel (editors), Computational Intelligence:
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1. 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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Optimization Problems”, IEEE Transactions on Systems, Man, and Cybernetics–Part B: Cybernetics, Vol. 38, No. 5,
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Optimization”, in Xavier Gandibleux & Matthias Ehrgott (editors), Multiple Criteria Optimization. State of
the Art Annotated Bibliographic Survey, Chapter 6, pp. 277-331, Kluwer’s International Series in Operations
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of Mathematical Psychology, Vol. 55, No. 5, pp. 386–396, October 2011.
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& Operations Research, Vol. 34, No. 11, pp. 3346–3361, November 2007.
3. Samya Elaoud, Taicir Loukil and Jacques Teghem, “The Pareto fitness genetic algorithm: Test function study”, European
Journal of Operational Research, Vol. 177, No. 3, pp. 1703–1719, March 16, 2007.
• Ricardo Landa Becerra and Carlos A. Coello Coello, “A Cultural Algorithm for Solving the Job-Shop Scheduling
Problem”, en Yaochu Jin (editor) Knowledge Incorporation in Evolutionary Computation, Springer, pp.
37–55, Studies in Fuzziness and Soft Computing, Vol. 167, ISBN 3-540-22902-7, 2005.
1. Jesus Garcia, Antonio Berlanga and Jose M. Molina, “Evolutionary algorithms in multiply-specified engineering. The
MOEAs and WCES strategies”, Advanced Engineering Informatics, Vol. 21, No. 1, pp. 3–21, January 2007.
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Academic Publishers, Boston, ISBN 0-7923-7654-4, February 2002.
1. Marcelo H. Kobayashi, “On a biologically inspired topology optimization method”, Communications in Nonlinear Science
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optimization of engineering problems”, Engineering Optimization, Vol. 43, No. 1, pp. 39–59, January 2011.
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Trends in Evolutionary Multiobjective Optimization”, in Manuel Graña, Richard Duro, Alicia d’Anjou, and
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Objective Metaheuristics to Public Portfolio Selection Through Multidimensional Modelling of Social Return”, Gestion
y Politica Publica, Vol. 20, No. 2, pp. 381–432, 2011.
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3. Deo Vidyarthi and Lutfi Khanbary, “Multi-objective optimization for channel allocation in mobile computing using
NSGA-II”, International Journal of Network Management, Vol. 21, No. 3, pp. 247–266, May 2011.
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5. J.M. Herrero, X. Blasco, M. Martinez, C. Ramos and J. Sanchis, “Non-linear robust identification of a greenhouse model
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evolutionary algorithms (MOEA): A reliability application”, Reliability Engineering & System Safety, Vol. 92, No. 6,
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7. Diego Sal and Manuel Graña, “Hyperspectral image watermarking with an evolutionary algorithm”, Knowledge-Based
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Intelligence Vol. 3681, 2005.
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sonic crystal attenuation properties by ev-MOGA multiobjective evolutionary algorithm”, Structural and Multidisciplinary
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10. 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
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• Carlos A. Coello Coello, “Recent Trends in Evolutionary Multiobjective Optimization”, in Ajith Abraham,
Lakhmi Jain and Robert Goldberg (editors), Evolutionary Multiobjective Optimization: Theoretical Advances
And Applications, pp. 7–32, Springer-Verlag, London, 2005, ISBN 1-85233-787-7.
1. 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.
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2. 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.
3. Nhu Binh Ho and Joc Cing Tay, “Solving multiple-objective flexible job shop problems by evolution and local search”,
IEEE Transactions on Systems, Man, and Cybernetics Part C–Applications and Reviews, Vol. 38, No. 5, pp. 674–685,
September 2008.
4. Joc Cing Tay and Nhu Binh Ho, “Evolving dispatching rules using genetic programming for solving multi-objective
flexible job-shop problems”, Computers & Industrial Engineering, Vol. 54, No. 3, pp. 453–473, April 2008.
5. Hui Li and Qingfu Zhang, “A Multiobjective Differential Evolution Based on Decomposition for Multiobjective Optimization
with Variable Linkages”, in Thomas Philip Runarsson, Hans-Georg Beyer, Edmund Burke, Juan J. Merelo-Guervós,
L. Darrell Whitley and Xin Yao (editors), Parallel Problem Solving from Nature - PPSN IX, 9th International Conference,
pp. 583–592, Springer. Lecture Notes in Computer Science Vol. 4193, Reykjavik, Iceland, September 2006.
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7. 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.
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clouds”, Software–Practice & Experience, Vol. 41, No. 5, pp. 469–493, April 2011.
9. Juan C. Vidal, Manuel Mucientes, Alberto Bugarín 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.
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design optimization”, Mathematical and Computer Modelling, Vol. 52, Nos. 11-12, pp. 1966–1975, December 2010.
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Evolutionary Computation”, Applied Soft Computing, Vol. 11, No. 1, pp. 356–364, January 2011.
12. Ricardo Perera and Sheng-En Fang, “Influence of Objective Functions in Structural Damage Identification using Refined
and Simple Models”, International Journal of Structural Stability and Dynamics, Vol. 9, No. 4, pp. 607–625, December
2009.
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13. Andreas Efstratiadis and Demetris Koutsoyiannis, “One decade of multi-objective calibration approaches in hydrological
modelling: a review”, Hydrological Sciences Journal–Journal Des Sciences Hydrologiques, Vol. 55, No. 1, pp. 58–78,
2010.
14. Elisabete Figueiredo, Sandra Valente, Celeste Coelho and Luisa Pinho, “Coping with risk: analysis on the importance
of integrating social perceptions on flood risk into management mechanisms - the case of the municipality of Agueda,
Portugal”, Journal of Risk Research, Vol. 12, No. 5, pp. 581–602, 2009.
15. Ricardo Perera, Antonio Ruiz and Carlos Manzano, “Performance assessment of multicriteria damage identification
genetic algorithms”, Computers & Structures, Vol. 87, Nos. 1-2, pp. 120–127, January 2009.
16. Ricardo Perera, Sheng-En Fang and C. Huerta, “Structural crack detection without updated baseline model by single
and multiobjective optimization”, Mechanical Systems and Signal Processing, Vol. 23, No. 3, pp. 752–768, April 2009.
17. Maoguo Gong, Licheng Jiao, Haifeng Du and Liefeng Bo, “Multiobjective immune algorithm with nondominated
neighbor-based selection”, Evolutionary Computation, Vol. 16, No. 2, pp. 225–255, Summer 2008.
18. Ricardo Perera and Antonio Ruiz, “A multistage FE updating procedure for damage identification in large-scale structures
based on multiobjective evolutionary optimization”, Mechanical Systems and Signal Processing, Vol. 22, No. 4,
pp. 970–991, May 2008.
19. Ricardo Perera, Antonio Ruiz and Carlos Manzano, “An evolutionary multiobjective framework for structural damage
localization and quantification”, Engineering Structures, Vol. 29, No. 10, pp. 2540–2550, October 2007.
20. Siew-Chin Neoh, Norhashimah Morad, Chee-Peng Lim and Zalina Abdul Aziz, “A Layered-Encoding Cascade Optimization
Approach to Product-Mix Planning in High-Mix-Low-Volume Manufacturing”, IEEE Transactions on Systems,
Man, and Cybernetics Part A—Systems and Humans, Vol. 40, No. 1, pp. 133–146, January 2010.
21. Jing Tian and Lincheng Shen, “A multi-objective evolutionary algorithm for multi-UAV cooperative reconnaissance
problem”, Neural Information Processing, Part 3, Proceedings, pp. 900–909, Springer, Lecture Notes in Computer
Science Vol. 4234, 2006.
22. Pedro Sousa, Miguel Rocha, Miguel Rio and Paulo Cortez, “Efficient OSPF weight allocation for intra-domain QoS
optimization”, Autonomic Principles of IP Operations and Management, Proceedings, pp. 37–48, Springer, Lecture
Notes in Computer Science Vol. 4268, 2006.
23. David Coulot, Arnaud Pollet, Xavier Collilieux and Philippe Berio, “Global optimization of core station networks for
space geodesy: application to the referencing of the SLR EOP with respect to ITRF”, Journal of Geodesy, Vol. 84, No.
1, pp. 31–50, January 2010.
24. Gideon Avigad and Amiram Moshaiov, “Interactive Evolutionary Multiobjective Search and Optimization of Set-Based
Concepts”, IEEE Transactions on Systems, Man, and Cybernetics Part B–Cybernetics, Vol. 39, No. 4, pp. 1013–1027,
August 2009.
25. 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.
26. 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.
27. 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.
• Carlos A. Coello Coello, “Evolutionary Multiobjective Optimization: Current and Future Challenges”, in
Jose Benitez, Oscar Cordon, Frank Hoffmann and Rajkumar Roy (editors), Advances in Soft Computing—
Engineering, Design and Manufacturing, pp. 243–256, Springer-Verlag, ISBN 1-85233-755-9, September
2003.
1. Peter von Buelow, “Suitability of genetic based exploration in the creative design process”, Digital Creativity, Vol. 19,
No. 1, pp. 51–61, 2008.
2. 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.
3. Maoguo Gong, Licheng Jiao, Haifeng Du and Liefeng Bo, “Multiobjective immune algorithm with nondominated
neighbor-based selection”, Evolutionary Computation, Vol. 16, No. 2, pp. 225–255, Summer 2008.
4. Antonio Pinto, Daniele Peri and Emilio F. Campana, “Multiobjective optimization of a containership using deterministic
particle swarm optimization”, Journal of Ship Research, Vol. 51, No. 3, pp. 217–228, September 2007.
5. Wangshu Yao, Chen Shifu and Chen Zhaoqian, “SDMOGA: A New Multi-objective Genetic Algorithm Based on Objective
Space Divided”, in Irwin King, Jun Wang, Laiwan Chan and DeLiang L. Wang (editors), Neural Information
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6. L. Grandinetti, F. Guerriero, G. Lepera and M. Mancini, “A niched genetic algorithm to solve a pollutant emission
reduction problem in the manufacturing industry: A case study”, Computers & Operations Research, Vol. 34, No. 7,
pp. 2191–2214, July 2007.
7. MaoGuo Gong, LiCheng Jiao, WenPing Ma and HaiFeng Du, “Multiobjective optimization using an immunodominance
and clonal selection inspired algorithm”, Science in China Series F–Information Sciences, Vol. 51, No. 8, pp. 1064–1082,
August 2008.
• Dragan Cvetkovic and Carlos A. Coello Coello, “Human Preferences and Their Applications in Evolutionary
Multi-Objective Optimization”, en Yaochu Jin (editor) Knowledge Incorporation in Evolutionary Computation,
Springer, pp. 479–502, Studies in Fuzziness and Soft Computing, Vol. 167, ISBN 3-540-22902-7,
2005.
1. David Coulot, Arnaud Pollet, Xavier Collilieux and Philippe Berio, “Global optimization of core station networks for
space geodesy: application to the referencing of the SLR EOP with respect to ITRF”, Journal of Geodesy, Vol. 84, No.
1, pp. 31–50, January 2010.
• Efrén 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
Solving from Nature: From Concepts to Applications, pp. 53–75, Springer, 2008, ISBN 978-3-540-72963-1.
1. Romanas Puisa and Heinrich Streckwall, “Prudent constraint-handling technique for multiobjective propeller optimisation”,
Optimization and Engineering, Vol. 12, No. 4, pp. 657–680, December 2011.
2. Andreas Konstantinidis and Kun Yang, “Multi-objective K-connected Deployment and Power Assignment in WSNs
using a problem-specific constrained evolutionary algorithm based on decomposition”, Computer Communications, Vol.
34, No. 1, pp. 83–98, January 15, 2011.
3. Yong Wang, Zixing Cai and Yuren Zhou, “Accelerating adaptive trade-off model using shrinking space technique for
constrained evolutionary optimization”, International Journal for Numerical Methods in Engineering, Vol. 77, No. 11,
pp. 1501–1534, March 2009.
4. 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.
Journals Internacionales
• Efrén Mezura-Montes and Carlos A. Coello Coello, “Constraint-Handling in Nature-Inspired Numerical
Optimization: Past, Present and Future”, Swarm and Evolutionary Computation, Vol. 1, No. 4, pp. 173–
194, December 2011.
1. Nebojsa Bacanin and Milan Tuba, “Artificial Bee Colony (ABC) Algorithm for Constrained Optimization Improved
with Genetic Operators”, Studies in Informatics and Control, Vol. 21, No. 2, pp. 137–146, June 2012.
• Victoria S. Aragón, Susana C. Esquivel and Carlos A. Coello Coello, “A modified version of a T-Cell Algorithm
for constrained optimization problems”, International Journal for Numerical Methods in Engineering, Vol.
84, No. 3, pp. 351–378, 15 October 2010.
1. Amir Hossein Gandomi, Xin-She Yang, Siamak Talatahari and Suash Deb, “Coupled eagle strategy and differential
evolution for unconstrained and constrained global optimization”, Computers & Mathematics with Applications, Vol.
63, No. 1, pp. 191–200, January 2012.
• J.E. Mendoza, M.E. López, C.A. Coello Coello and E.A. López, “Microgenetic multiobjective reconfiguration
algorithm considering power losses and reliability indices for medium voltage distribution network”, IET
Generation, Transmission & Distribution, Vol. 3, No. 9, pp. 825-840, September 2009.
1. Peng Zhang, Wenyuan Li and Shouxiang Wang, “Reliability-oriented distribution network reconfiguration considering
uncertainties of data by interval analysis”, International Journal of Electrical Power & Energy Systems, Vol. 34, No. 1,
pp. 138–144, January 2012.
• Xiaolin Hu, Carlos A. Coello Coello and Zhangcan Huan, “A new multi-objective evolutionary algorithm:
neighbourhood exploring evolution strategy”, Engineering Optimization, Vol. 37, No. 4, pp. 351–379, June
2005.
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1. 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.
• Alfredo G. Hernández-Díaz, Luis V. Santana-Quintero, Carlos A. Coello Coello, Julián Molina and Rafael
Caballero, “Improving the efficiency of ɛ-dominance based grids”, Information Sciences, Vol. 181, No. 15,
pp. 3101–3129, 1 August 2011.
1. 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.
• Antonin Ponsich and Carlos A. Coello Coello, “Differential Evolution performances for the solution of mixed
integer constrained Process Engineering problems”, Applied Soft Computing, Vol. 11, No. 1, pp. 399–409,
January 2011.
1. E. Zio, L.R. Golea and G. Sansavini, “Optimizing protections against cascades in network systems: A modified binary
differential evolution algorithm”, Reliability Engineering & System Safety, Vol. 103, pp. 72–83, July 2012.
2. D. Iranshahi, E. Pourazadi, K. Paymooni and M.R. Rahimpour, “Utilizing DE optimization approach to boost hydrogen
and octane number in a novel radial-flow assisted membrane naphtha reactor”, Chemical Engineering Science, Vol. 68,
No. 1, pp. 236–249, January 22, 2012.
3. Xianhui Zeng, Wai-Keung Wong and Sunney Yung-Sun Leung, “An operator allocation optimization model for balancing
control of the hybrid assembly lines using Pareto utility discrete differential evolution algorithm”, Computers &
Operations Research, Vol. 39, No. 5, pp. 1145–1159, May 2012.
4. Leandro dos Santos Coelho and Marcelo Wicthoff Pessoa, “A tuning strategy for multivariable PI and PID controllers
using differential evolution combined with chaotic Zaslavskii map”, Expert Systems with Applications, Vol. 38, No. 11,
pp. 13694–13701, October 2011.
5. D. Iranshahi, A.M. Bahmanpour, K. Paymooni, M.R. Rahimpour and A. Shariati, “Simultaneous hydrogen and aromatics
enhancement by obtaining optimum temperature profile and hydrogen removal in naphtha reforming process; a novel
theoretical study”, International Journal of Hydrogen Energy, Vol. 36, No. 14, pp. 8316–8326, July 2011.
• E. Mezura-Montes, C. A. Coello Coello, J. Velázquez-Reyes and L. Muñoz-Dávila, “Multiple trial vectors in
differential evolution for engineering design”, Engineering Optimization, Vol. 39, No. 5, pp. 567-589, July
2007.
1. Adam Slowik, “Application of an Adaptive Differential Evolution Algorithm With Multiple Trial Vectors to Artificial
Neural Network Training”, IEEE Transactions on Industrial Electronics, Vol. 58, No. 8, pp. 3160–3167, August 2011.
• Eduardo Fernández, Edy López, Sergio Bernal, Carlos A. Coello Coello and Jorge Navarro, “Evolutionary
multiobjective optimization using an outranking-based dominance generalization”, Computers & Operations
Research, Vol. 37, No. 2, pp. 390–395, February 2010.
1. Ozgur Kabak and Da Ruan, “A comparison study of fuzzy MADM methods in nuclear safeguards evaluation”, Journal
of Global Optimization, Vol. 51, No. 2, pp. 209–226, October 2011.
• Mario Villalobos-Arias, Carlos A. Coello Coello and Onésimo Hernández-Lerma, “Asymptotic Convergence of
Metaheuristics for Multiobjective Optimization Problems”, Soft Computing, Vol. 10, No. 11, pp. 1001–1005,
September 2006.
1. Yu Chen, Xiufen Zou and Weicheng Xie, “Convergence of multi-objective evolutionary algorithms to a uniformly distributed
representation of the Pareto front”, Information Sciences, Vol. 181, No. 16, pp. 3336–3355, August 15,
2011.
• Oliver Schütze, Carlos A. Coello Coello, Sanaz Mostaghim, El-Ghazali Talbi and Michael Dellnitz, “Hybridizing
Evolutionary Strategies with Continuation Methods for Solving Multi-Objective Problems”, Engineering
Optimization, Vol. 40, No. 5, pp. 383–402, May 2008.
1. Ahmad Nourbakhsh, Hamed Safikhani and Shahram Derakhshan, “The comparison of multi-objective particle swarm
optimization and NSGA II algorithm: applications in centrifugal pumps”, Engineering Optimization, Vol. 43, No. 10,
pp. 1095–1113, 2011.
2. Peter A. N. Bosman, “On Gradients and Hybrid Evolutionary Algorithms for Real-Valued Multiobjective Optimization”,
IEEE Transactions on Evolutionary Computation, Vol. 16, No. 1, pp. 51–69, February 2012.
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3. Yu Chen, Xiufen Zou and Weicheng Xie, “Convergence of multi-objective evolutionary algorithms to a uniformly distributed
representation of the Pareto front”, Information Sciences, Vol. 181, No. 16, pp. 3336–3355, August 15,
2011.
• Victoria S. Aragón, Susana C. Esquivel and Carlos A. Coello Coello, “Optimizing Constrained Problems
through a T-Cell Artificial Immune System”, Journal of Computer Science & Technology, Vol. 8, No. 3, pp.
158–165, 2008.
1. 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.
• Carlos A. Coello Coello, “Evolutionary Multi-Objective Optimization: Some Current Research Trends and
Topics that Remain to be Explored”, Frontiers of Computer Science in China, Vol. 3, No. 1, pp. 18–30,
2009.
1. C.W. Bong and M. Rajeswari, “Multiobjective clustering with metaheuristic: current trends and methods in image
segmentation”, IET Image Processing, Vol. 6, No. 1, pp. 1–10, February 2012.
2. Romanas Puisa and Heinrich Streckwall, “Prudent constraint-handling technique for multiobjective propeller optimisation”,
Optimization and Engineering, Vol. 12, No. 4, pp. 657–680, December 2011.
3. Chi Zhang, Jose Emmanuel Ramirez-Marquez and Claudio M. Rocco Sanseverino, “A holistic method for reliability
performance assessment and critical components detection in complex networks”, IIE Transactions, Vol. 43, No. 9, pp.
661–675, 2011.
4. Claudio M. Rocco, Jose Emmanuel Ramirez-Marquez, Daniel E. Salazar and Cesar Yajure, “Assessing the Vulnerability
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5. Chin-Wei Bong and Mandava Rajeswari, “Multi-objective nature-inspired clustering and classification techniques for
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6. James Bekker and Chris Aldrich, “The cross-entropy method in multi-objective optimisation: An assessment”, European
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7. S.I. Sulaiman, T.K.A. Rahman and I. Musirin, “Multi-Objective Evolutionary Programming for Optimal Grid-Connected
Photovoltaic System Design”, International Review of Electrical Engineering–IREE, Part B, Vol. 5, No. 6, pp. 2936–
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• Luis V. Santana-Quintero, Alfredo G. Hernández-Díaz, Julián Molina, Carlos A. Coello Coello and Rafael
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2. 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.
3. Swagatam Das and Ponnuthurai Nagaratnam Suganthan, “Differential Evolution: A Survey of the State-of-the-Art”,
IEEE Transactions on Evolutionary Computation, Vol. 15, No. 1, pp. 27–54, February 2011.
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System Heuristic for Generating Short Addition Chains”, IEEE Transactions on Evolutionary Computation,
Vol. 12, No. 1, pp. 1–24, February 2008.
1. Yin Li, Gong-Liang Chen, Yi-Yang Chen and Jian-Hua Li, “An improvement of the TyT algorithm for GF(2(M)) Based
on Reusing Intermediate Computation Results”, Communications in Mathematical Sciences, Vol. 9, No. 1, pp. 277–287,
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Problems with an Algorithm Inspired on the Ant Colony Metaphor”, IEEE Transactions on Evolutionary
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1. Abu S.S.M. Barkat Ullah, Ruhul Sarker and Chris Lokan, “Handling equality constraints in evolutionary optimization”,
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2. Haibo Zhang and G.P. Rangaiah, “An efficient constraint handling method with integrated differential evolution for
numerical and engineering optimization”, Computers & Chemical Engineering, Vol. 37, pp. 74–88, February 10, 2012.
3. Chih-Ming Hsu, “Applying genetic programming and ant colony optimisation to improve the geometric design of a
reflector”, International Journal of Systems Science, Vol. 43, No. 5, pp. 972–986, 2012.
4. Ali Husseinzadeh Kashan, “An efficient algorithm for constrained global optimization and application to mechanical
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December 2011.
5. David B. Fogel, “Revisiting Overlooked Foundations of Evolutionary Computation: Part I”, Cybernetics and Systems,
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Pressure Towards the Best Compromise in Evolutionary Multiobjective Optimization: The Extended NOSGA
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1. Liang Huang, Il Hong Suh and Ajith Abraham, “Dynamic multi-objective optimization based on membrane computing
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2. Sultan Noman Qasem and Siti Mariyam Shamsuddin, “Memetic Elitist Pareto Differential Evolution algorithm based
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3. Jun Wang, Hong Peng and Peng Shi, “An optimal image watermarking approach based on a multi-objective genetic
algorithm”, Information Sciences, Vol. 181, No. 24, pp. 5501–5514, December 15, 2011.
4. Rodrigo C. Barros, Duncan D. Ruiz and Marcio P. Basgalupp, “Evolutionary model trees for handling continuous classes
in machine learning”, Information Sciences, Vol. 181, No. 5, pp. 954–971, March 1, 2011.
• Enrique Alba, Gabriel Luque, Carlos A. Coello Coello and Erika Hernández Luna, “A Comparative Study
of Serial and Parallel Heuristics Used to Design Combinational Logic Circuits”, Optimization Methods and
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Hydrothermal Scheduling”, IEEE Transactions on Power Systems, Vol. 27, No. 1, pp. 142–152, February 2012.
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6. N.B. Muthuselvan, M. Devesh Raj and P. Somasundaram, “Cauchy - Gaussian Infused Particle Swarm Optimization for
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golden section line search”, Mathematical Programming, Vol. 131, Nos. 1-2, pp. 131–161, February 2012.
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1. Vivek Kumar Mehta and Bhaskar Dasgupta, “A constrained optimization algorithm based on the simplex search
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2. Ahmad Mozaffari, Mofid Gorji-Bandpy and Tahereh B. Gorji, “Optimal design of constraint engineering systems: application
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3. Xin-She Yang and Suash Deb, “Two-stage eagle strategy with differential evolution”, International Journal of Bio-
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1. Jianyong Chen, Qiuzhen Lin and LinLin Shen, “An Immune-Inspired Evolution Strategy for Constrained Optimization
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1. Kaiquan Cai, Jun Zhang, Chi Zhou, Xianbin Cao and Ke Tang, “Using computational intelligence for large scale air
route networks design”, Applied Soft Computing, Vol. 12, No. 9, pp. 2790–2800, September 2012.
2. Chunhua Peng, Huijuan Sun, Jianfeng Guo and Gang Liu, “Multi-objective optimal strategy for generating and bidding
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11. Abolfazl Khalkhali, Mehdi Farajpoor and Hamed Safikhani, “Modeling and Multi-Objective Optimization of Forward-
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