S. -Z. ZhaoP. N. SuganthanQuan-Ke PanM. Fatih TasgetirenSuganthan, P.N.Tasgetiren, M. FatihZhao, S.-Z.Fatih Tasgetiren, M.Pan, Quan-Ke2025-10-0620110957-41741873-679310.1016/j.eswa.2010.09.0322-s2.0-78650680946http://dx.doi.org/10.1016/j.eswa.2010.09.032https://gcris.yasar.edu.tr/handle/123456789/7502https://doi.org/10.1016/j.eswa.2010.09.032In this paper the dynamic multi-swarm particle swarm optimizer (DMS-PSO) is improved by hybridizing it with the harmony search (HS) algorithm and the resulting algorithm is abbreviated as DMS-PSO-HS. We present a novel approach to merge the HS algorithm into each sub-swarm of the DMS-PSO. Combining the exploration capabilities of the DMS-PSO and the stochastic exploitation of the HS the DMS-PSO-HS is developed. The whole DMS-PSO population is divided into a large number of small and dynamic sub-swarms which are also individual HS populations. These sub-swarms are regrouped frequently and information is exchanged among the particles in the whole swarm. The DMS-PSO-HS demonstrates improved on multimodal and composition test problems when compared with the DMS-PSO and the HS. (C) 2010 Elsevier Ltd. All rights reserved.Englishinfo:eu-repo/semantics/closedAccessParticle swarm optimizer, Dynamic multi-swarm particle swarm optimizer, Harmony search, Dynamic sub-swarms, Numerical optimization, Multimodal optimizationHarmony SearchDynamic Multi-Swarm Particle Swarm OptimizerMultimodal OptimizationParticle Swarm OptimizerDynamic Sub-SwarmsNumerical OptimizationArticle