A competitive and cooperative co-evolutionary approach to multi-objective particle swarm optimization algorithm design

European Journal of Operational Research

Volumn 202, Issue 1, 2010, Pages 42-54

  Goh, C K ^a   Tan, K C ^b   Liu, D S ^b   Chiam, S C ^b  

^a ROLLS ROYCE SINGAPORE PTE LTD   (Singapore)

^b NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

Author keywords

Competitive cooperative co evolution; Multi objective optimization; Particle swarm optimization

Indexed keywords

CO-EVOLUTION; CO-EVOLUTIONARY; CO-EVOLUTIONARY APPROACH; COMPETITIVE-COOPERATIVE CO-EVOLUTION; COMPLEX OPTIMIZATION; CONVERGENCE SPEED; COOPERATIVE CO-EVOLUTION; MULTI OBJECTIVE ALGORITHM; MULTI OBJECTIVE PARTICLE SWARM OPTIMIZATION; OPTIMIZATION TECHNIQUES; OTHER ALGORITHMS; PREMATURE CONVERGENCE; PROBLEM DECOMPOSITION; RESEARCH COMMUNITIES; SIMULATION RESULT;

ALGORITHMS; MULTIOBJECTIVE OPTIMIZATION; TRAJECTORIES;

PARTICLE SWARM OPTIMIZATION (PSO);

EID: 70349843699     PISSN: 03772217     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ejor.2009.05.005     Document Type: Article

References (36)

1. C.A.C. Coello, M.R. Sierra, A co-evolutionary multi-objective evolutionary algorithm, in: Proceedings of 2003 Congress on Evolutionary Computation, vol. 1, 2003, pp. 482-489.
2. Coello C.A., and Lechuga M.S. Handling multiple objectives with particle swarm optimization. IEEE Transaction on Evolutionary Computation 8 3 (2004) 256-279
3. Deb K. Multi-objective genetic algorithms: Problem difficulties and construction of test problem. Evolutionary Computation 7 3 (1999) 205-230
4. Deb K., Pratap A., Agarwal S., and Meyarivan T. A fast and elitist multi-objective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation 6 2 (2002) 182-197
5. Fieldsend J.E., Everson R.M., and Singh S. Using unconstrained elite archives for multiobjective optimization. IEEE Transactions on Evolutionary Computation 7 3 (2003) 305-323
6. Goh C.K., and Tan K.C. An investigation on noisy environments in evolutionary multiobjective optimization. IEEE Transactions on Evolutionary Computation 11 3 (2007) 354-381
7. Goh C.K., and Tan K.C. A competitive-cooperative coevolutionary paradigm for dynamic multi-objective optimization. IEEE Transactions on Evolutionary Computation 13 1 (2009) 103-127
8. E.J. Hughes, Evolutionary many-objective optimisation: Many once or one many? in: Proceedings of 2005 IEEE Congress on Evolutionary Computation, vol. 1, 2005, pp. 222-227.
9. A. Iorio, X. Li, A cooperative co-evolutionary multi-objective algorithm using non-dominated sorting, in: Proceedings of Genetic and Evolutionary Computation Conference 2004, Lecture Notes in Computer Science, 2004, pp. 537-548.
10. N. Keerativuttitumrong, N. Chaiyaratana, V. Varavithya, Multi-objective cooperative co-evolutionary genetic algorithm, in: Proceedings of Parallel Problem Solving From Nature VII, Lecture.
11. V. Khare, X. Yao, K. Deb, Performance scaling of multi-objective evolutionary algorithms, in: Proceedings of the Second International Conference on Evolutionary Multi-criterion Optimization, 2003, pp. 376-390.
12. Khor E.F., Tan K.C., Lee T.H., and Goh C.K. A study on distribution preservation mechanism in evolutionary multi-objective optimization. Artificial Intelligence Review 23 1 (2005) 31-56
13. Knowles J.D., and Corne D.W. Approximating the nondominated front using Pareto archived evolutionary strategy. Evolutionary Computation 8 2 (2000) 149-172
14. J. Lohn, W.F. Kraus, G.L. Haith, Comparing a co-evolutionary genetic algorithm for multi-objective optimization, in: Proceedings of 2002 Congress on Evolutionary Computation, 2002, pp. 1157-1162.
15. S. Mostaghim, J. Teich, Strategies for finding good local guides in multi-objective particle swarm optimization (MOPSO), in: Proceedings of 2003 IEEE Swarm Intelligence Symposium, 2003, pp. 26-33.
16. Liu D.S., Tan K.C., Goh C.K., and Ho W.K. A multiobjective memetic algorithm based on particle swarm optimization. IEEE Transactions on Systems, Man and Cybernetics: Part B (Cybernetics) 37 1 (2007) 42-50
17. Liu D.S., Tan K.C., Huang S.Y., Goh C.K., and Ho W.K. On solving multiobjective bin packing problems using evolutionary particle swarm optimization. European Journal of Operational Research 190 2 (2008) 357-382
18. K. Maneeratana, K. Boonlong, N. Chaiyaratana, Multi-objective optimisation by co-operative co-evolution, in: Proceedings of Eighth International Conference on Parallel Problem Solving from Nature, 2004, pp. 772-781.
19. J.R. Scott, Fault tolerant design using single and multi-criteria genetic algorithms, Masters Thesis, Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, 1995.
20. Potter M.A., and De Jong K.A. Cooperative co-evolution: An architecture for evolving coadapted subcomponents. Evolutionary Computation 8 1 (2000) 1-29
21. M.A. Potter, The design and analysis of a computational model of cooperative co-evolution, Ph.D. Thesis, George Mason University, 1997.
22. Rosin C.D., and Belew R.K. New methods for competitive co-evolution. Evolutionary Computation 5 1 (1997) 1-29
23. Y. Shi, R. Eberhart, Parameter selection in particle swarm optimization, in: Proceedings of the Seventh Annual Conference on Evolutionary Programming, 1998, pp. 591-601.
24. Tan K.C., Goh C.K., Mamun A.A., and Ei E.Z. An evolutionary artificial immune system for multi-objective optimization. European Journal of Operational Research 187 2 (2008) 371-392
25. Tan K.C., Cheong C.Y., and Goh C.K. Solving multiobjective vehicle routing problem with stochastic demand via evolutionary computation. European Journal of Operational Research 177 (2007) 813-839
26. Tan K.C., Chew Y.H., and Lee L.H. A hybrid multiobjective evolutionary algorithm for solving truck and trailer vehicle routing problems. European Journal of Operational Research 172 (2006) 855-885
27. Tan K.C., Yang Y.J., and Goh C.K. A distributed cooperative co-evolutionary algorithm for multi-objective optimization. IEEE Transactions on Evolutionary Computation 10 5 (2006) 527-549
28. Tan K.C., Khor E.F., Lee T.H., and Sathikannan R. An evolutionary algorithm with advanced goal and priority specification for multiobjective optimization. Journal of Artificial Intelligence Research 18 (2003) 183-215
29. Tan K.C., Lee T.H., and Khor E.F. Evolutionary algorithms with dynamic population and local exploration for multiobjective optimization. IEEE Transactions on Evolutionary Computation 5 6 (2001) 565-588
30. van den Bergh F., and Engelbrecht A.P. A cooperative approach to particle swarm optimization. IEEE Transaction on Evolutionary Computation 8 3 (2004) 225-239
31. G. Venter, R.T. Haftka, A two species genetic algorithm for designing composite laminates subjected to uncertainty, in: Proceedings of 37th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, 1996, pp. 1848-1857.
32. E. Zitzler, M. Laumanns, L. Thiele, SPEA2: Improving the strength pareto evolutionary algorithm, Technical Report 103, Gloriastrasse 35, CH-8092 Zurich, Switzerland, 2001.
33. Tseng C.T., and Liao C.J. A discrete particle swarm optimization for lot-streaming flowshop scheduling problem. European Journal of Operational Research 191 2 (2008) 360-373
34. Lee L.H., Chew E.P., Teng S.Y., and Chen Y.K. Multi-objective simulation-based evolutionary algorithm for an aircraft spare parts allocation problem. European Journal of Operational Research 189 2 (2008) 476-491
35. Ishibuchi H., Narukawa K., Tsukamoto N., and Nojima Y. An empirical study on similarity-based mating for evolutionary multiobjective combinatorial optimization. European Journal of Operational Research 188 1 (2008) 57-75
36. Neumann F. Expected runtimes of a simple evolutionary algorithm for the multi-objective minimum spanning tree problem. European Journal of Operational Research 181 3 (2007) 1620-1629