A swarm metaphor for multiobjective design optimization

Engineering Optimization

Volumn 34, Issue 2, 2002, Pages 141-153

  Ray, Tapabrata ^a   Liew, K M ^a  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

Author keywords

Constrained optimization; Multiobjective optimization; Pareto solutions; Swarm

Indexed keywords

DESIGN; GENETIC ALGORITHMS; MATHEMATICAL OPERATORS; MATRIX ALGEBRA; PARETO PRINCIPLE; VECTORS;

MULTIOBJECTIVE DESIGN OPTIMIZATION; NONDOMINATED SORTING GENETIC ALGORITHM; PARETO SOLUTIONS; SWARM METAPHOR;

OPTIMIZATION;

EID: 0036522301     PISSN: 0305215X     EISSN: None     Source Type: Journal    
DOI: 10.1080/03052150210915     Document Type: Article

References (17)

1. Angeline, P. (1998). Evolutionary optimization versus particle swarm optimization: Philosophy and performance differences. Proceedings of the Seventh Annual Conference on Evolutionary Programming. San Diego, pp. 601-610.
2. Cheng, F.Y. and Li, X.S. (1999). Generalized method for multiobjective engineering optimization. Engineering Optimization, 31, 641-661.
3. Coello, C.A.C. (1999). An updated survey of evolutionary multiobjective optimization techniques: State of the art and future trends. Proceedings of the 1999 Congress on Evolutionary Computation. Washington, pp. 3-13.
4. Deb, K. (1999). Evolutionary algorithms for multi-criterion optimization in engineering design. In Evolutionary Algorithms in Engineering and Computer Science. Wiley, pp. 135-161.
5. Deb, K. and Kumar, A. (1995). Real coded genetic algorithms with simulated binary crossover: Studies on multimodal and multiobjective problems. Complex Systems, 9(6), 431-454.
6. Deb, K., Agrawal, S., Pratap, A. and Meyarivan, T. (2000). A fast ellitist nondominated sorting genetic algorithm for multiobjective optimization: NSGA-II. Proceedings of Parallel Problem Solving from Nature VI. Springer, pp. 849-858.
7. Eberhart, R. and Shi, Y. (1998). Comparison between genetic algorithms and particle swarm optimization. Proceedings of the Seventh Annual Conference on Evolutionary Programming. Springer Verlag, pp. 611-618.
8. Fonseca, C.M. and Flemming, P.J. (1995), An overview of evolutionary algorithms in multiobjective optimization. Evolutionary Computation, 3(1), 1-16.
9. Fonseca, C.M. and Fleming, P.J. (1998). Multiobjective optimization and multiple constraint handling with evolutionary algorithms-Part I: A unified formulation. IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans, 28(1), 26-37.
10. Kennedy, J. and Eberhart, R.C. (1995). Particle swarm optimization. Proceedings of the 1995 IEEE International Conference on Neural Networks. IEEE Service Center, Piscataway, NJ, pp. 1942-1948.
11. Michalewicz, Z. and Schoenauer, M. (1996). Evolutionary algorithms for constrained parameter optimization problems. Evolutionary Computation, 4(1). 1-32.
12. Osyczka, A. and Kundu, S. (1995). A genetic algorithm-based multicriteria optimization method. Proceedings of First World Congress of Structural and Multidisciplinary Optimization. Elsevier Science, pp. 909-914.
13. Ray, T., Tai, K. and Seow, K.C. (2000). An evolutionary algorithm for constrained optimization. Proceedings of the Genetic and Evolutionary Computation Conference. GECCO 2000, Las Vegas, Morgan Kaufmann Publishers, pp. 771-777.
14. Ray, T., Tai, K. and Seow, K.C. (2001). Multiobjective design optimization by an evolutionary algorithm. Engineering Optimization, 33(4), 399-424.
15. Srinivas, N. and Deb, K. (1994). Multiobjective optimization using nondominated sorting in genetic algorithms. Evolutionary Computation, 2(3), 221-248.
16. Stadler, W. and Dauer, J. (1992). Multicriteria optimization in engineering: A tutorial and survey. Structural optimization: status and future. AIAA Journal, 209-249.
17. Surry, P., Radcliffe, N.J. and Boyd, I. (1995). A multiobjective approach to constrained optimization of gas supply networks. Proceedings of the AISB-95 Workshop on Evolutionary Computing, Vol. 993. Springer Verlag, pp. 166-180.