Shizheng ZhaoPonnuthurai Nagaratnam SuganthanQuanke PanM. Fatih Tasgetiren2025-10-062011095741740957-417410.1016/j.eswa.2010.09.032https://www.scopus.com/inward/record.uri?eid=2-s2.0-78650680946&doi=10.1016%2Fj.eswa.2010.09.032&partnerID=40&md5=e46dc72b0442434f4eff8d62bdfd2b84https://gcris.yasar.edu.tr/handle/123456789/10240In 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. © 2010 Elsevier Ltd. All rights reserved. © 2011 Elsevier B.V. All rights reserved.EnglishDynamic Multi-swarm Particle Swarm Optimizer, Dynamic Sub-swarms, Harmony Search, Multimodal Optimization, Numerical Optimization, Particle Swarm Optimizer, Dynamic Multi Swarms, Harmony Search, Hs Algorithm, Multi-modal, Multi-modal Optimization, Numerical Optimizations, Particle Swarm Optimizers, Sub-swarms, Test Problem, Algorithms, Optimization, Population Statistics, DiamondsDynamic multi swarms, Harmony search, HS algorithm, Multi-modal, Multi-modal optimization, Numerical optimizations, Particle swarm optimizers, Sub-swarms, Test problem, Algorithms, Optimization, Population statistics, DiamondsArticle