Multimodal function optimization based on particle swarm optimization

Author

Seo, Jang-Ho ; Im, Chang-Hwan ; Heo, Chang-Geun ; Kim, Jae-Kwang ; Jung, Hyun-Kyo ; Lee, Cheol-Gyun

Author_Institution

Sch. of Electr. Eng. & Comput. Sci., Seoul Nat. Univ.

Volume

42

Issue

4

fYear

2006

fDate

4/1/2006 12:00:00 AM

Firstpage

1095

Lastpage

1098

Abstract

In this paper, a new algorithm for the multimodal function optimization is proposed, based on the particle swarm optimization (PSO). A new method, named the multigrouped particle swarm optimization (MGPSO), keeps basic concepts of the PSO, and, thus, shows a more straightforward convergence compared to conventional hybrid type approaches. Moreover, the MGPSO has a unique advantage in that one can search N superior peaks of a multimodal function when the number of groups is N. The usefulness of the proposed algorithm was verified by the application to various case studies, including a practical electromagnetic optimization problem

Keywords

particle swarm optimisation; electromagnetic optimization problem; multigrouped particle swarm optimization; multimodal function optimization; Biomedical engineering; Birds; Computational efficiency; Computer science; Convergence; Evolutionary computation; Genetic algorithms; Genetic mutations; Particle swarm optimization; Telecommunications; Electromagnetic optimization problems; multigrouped particle swarm optimization (MGPSO); multimodal function optimization; particle swarm optimization (PSO);

fLanguage

English

Journal_Title

Magnetics, IEEE Transactions on

Publisher

ieee

ISSN

0018-9464

Type

jour

DOI

10.1109/TMAG.2006.871568

Filename

1608401