Cluster-structured Particle Swarm Optimization with interaction
Kazuyuki Yazawa, Makoto Motoki, Keiichiro Yasuda · 2009 ICCAS-SICE · 2009
A new cluster-structured Particle Swarm Optimization (PSO) with interaction and diversity of parameters is proposed in this paper. A swarm of PSO is divided into some sub-swarms (clusters), and not only interactions between sub-swarms and but also diversity of PSO parameters are added so as to improve the search ability of PSO. The cluster structure and the interaction of the proposed PSO are analyzed through some numerical simulations. The feasibility and the advantage of the proposed cluster-structured PSO are demonstrated through numerical simulations using four typical optimization test problems.