Multimodal function optimization based on particle swarm optimization

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

Research output: Contribution to journalArticlepeer-review

209 Scopus citations

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.

Original languageEnglish
Pages (from-to)1095-1098
Number of pages4
JournalIEEE Transactions on Magnetics
Volume42
Issue number4
DOIs
StatePublished - Apr 2006

Keywords

  • Electromagnetic optimization problems
  • Multigrouped particle swarm optimization (MGPSO)
  • Multimodal function optimization
  • Particle swarm optimization (PSO)

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