Multimodal function optimization based on particle swarm optimization
Jang-Ho Seo, Chang‐Hwan Im, Chang-Geun Heo, Jaekwang Kim, Hyun‐Kyo Jung, Cheol-Gyun Lee · IEEE Transactions on Magnetics · 2006
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.