Evolutionary algorithm with dynamic population size for multi-objective optimization

Author

Khor, E.F. ; Tan, K.C. ; Wang, M.L. ; Lee, T.H.

Author_Institution

Dept. ef Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore

Volume

4

fYear

2000

fDate

2000

Firstpage

2768

Abstract

Presents an incremental multiobjective evolutionary algorithm with dynamic population size that is adaptively computed according to the online discovered trade-off surface and its desired population distribution density. It incorporates the method of fuzzy boundary local perturbation with interactive local fine-tuning for broader neighborhood exploration to achieve better convergence as well as discovering any gaps or missing trade-off regions at each generation. The effectiveness of the proposed methodology is validated upon a benchmark multiobjective optimization problem

Keywords

convergence; evolutionary computation; optimisation; convergence; dynamic population size; evolutionary algorithm; fuzzy boundary local perturbation; incremental algorithm; interactive local fine-tuning; multi-objective optimization; population distribution density; trade-off surface; Convergence; Cost function; Distributed computing; Evolutionary computation; Heuristic algorithms; Optimization methods; Perturbation methods; Upper bound;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Electronics Society, 2000. IECON 2000. 26th Annual Confjerence of the IEEE

Conference_Location

Nagoya

Print_ISBN

0-7803-6456-2

Type

conf

DOI

10.1109/IECON.2000.972436

Filename

972436