A novel parallel multi-swarm algorithm based on comprehensive learning particle swarm optimization

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dc.contributor.authorGulcu, Saban
dc.contributor.authorKodaz, Halife
dc.date.accessioned2024-02-23T14:02:46Z
dc.date.available2024-02-23T14:02:46Z
dc.date.issued2015
dc.departmentNEÜen_US
dc.description.abstractThis article presented a parallel metaheuristic algorithm based on the Particle Swarm Optimization (PSO) to solve global optimization problems. In recent years, many metaheuristic algorithms have been developed. The PSO is one of them is very effective to solve these problems. But PSO has some shortcomings such as premature convergence and getting stuck in local minima. To overcome these shortcomings, many variants of PSO have been proposed. The comprehensive learning particle swarm optimizer (CLPSO) is one of them. We proposed a better variation of CLPSO, called the parallel comprehensive learning particle swarm optimizer (PCLPSO) which has multiple swarms based on the master-slave paradigm and works cooperatively and concurrently. The PCLPSO algorithm was compared with nine PSO variants in the experiments. It showed a great performance over the other PSO variants in solving benchmark functions including their large scale versions. Besides, it solved extremely fast the large scale problems. (C) 2015 Elsevier Ltd. All rights reserved.en_US
dc.identifier.doi10.1016/j.engappai.2015.06.013
dc.identifier.endpage45en_US
dc.identifier.issn0952-1976
dc.identifier.issn1873-6769
dc.identifier.scopus2-s2.0-84941140715en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage33en_US
dc.identifier.urihttps://doi.org/10.1016/j.engappai.2015.06.013
dc.identifier.urihttps://hdl.handle.net/20.500.12452/11845
dc.identifier.volume45en_US
dc.identifier.wosWOS:000362130500003en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherPergamon-Elsevier Science Ltden_US
dc.relation.ispartofEngineering Applications Of Artificial Intelligenceen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectParticle Swarm Optimizationen_US
dc.subjectParallel Algorithmen_US
dc.subjectComprehensive Learning Particle Swarm Optimizeren_US
dc.subjectGlobal Optimizationen_US
dc.titleA novel parallel multi-swarm algorithm based on comprehensive learning particle swarm optimizationen_US
dc.typeArticleen_US

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