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A niching co-swarm gravitational search algorithm for multi-modal optimization

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dc.contributor.authorYadav, A.-
dc.contributor.authorKim, J.H.-
dc.date.accessioned2021-09-04T23:52:50Z-
dc.date.available2021-09-04T23:52:50Z-
dc.date.created2021-06-17-
dc.date.issued2015-
dc.identifier.issn2194-5357-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/95896-
dc.description.abstractIn this paper, a Niching co-swarm gravitational search algorithm (CoGSA) is designed for solving multi-modal optimization problems. The collective approach of Gravitational Search Algorithm and differential evolution (DE) is used to solve multi-modal optimization problems. A set of twelve multi-modal problems are taken from a benchmark set of CEC 2013. An experimental study has been performed to evaluate the availability of CoGSA over these twelve problems. The performance is measured in an advanced way. It has been observed that CoGSA provides good solution for multi-modal optimization problems. © Springer India 2015.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherSpringer Verlag-
dc.subjectEvolutionary algorithms-
dc.subjectLearning algorithms-
dc.subjectOptimization-
dc.subjectAlgorithms-
dc.subjectSoft computing-
dc.subjectDifferential Evolution-
dc.subjectGravitational search algorithms-
dc.subjectMulti-modal-
dc.subjectMulti-modal optimization-
dc.subjectMultimodal problems-
dc.subjectAlgorithms-
dc.subjectProblem solving-
dc.titleA niching co-swarm gravitational search algorithm for multi-modal optimization-
dc.typeArticle-
dc.contributor.affiliatedAuthorKim, J.H.-
dc.identifier.doi10.1007/978-81-322-2217-0_48-
dc.identifier.scopusid2-s2.0-84926654286-
dc.identifier.bibliographicCitationAdvances in Intelligent Systems and Computing, v.335, pp.599 - 607-
dc.relation.isPartOfAdvances in Intelligent Systems and Computing-
dc.citation.titleAdvances in Intelligent Systems and Computing-
dc.citation.volume335-
dc.citation.startPage599-
dc.citation.endPage607-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalRegisteredClassscopus-
dc.subject.keywordPlusEvolutionary algorithms-
dc.subject.keywordPlusLearning algorithms-
dc.subject.keywordPlusOptimization-
dc.subject.keywordPlusAlgorithms-
dc.subject.keywordPlusSoft computing-
dc.subject.keywordPlusDifferential Evolution-
dc.subject.keywordPlusGravitational search algorithms-
dc.subject.keywordPlusMulti-modal-
dc.subject.keywordPlusMulti-modal optimization-
dc.subject.keywordPlusMultimodal problems-
dc.subject.keywordPlusAlgorithms-
dc.subject.keywordPlusProblem solving-
dc.subject.keywordAuthorDifferential evolution-
dc.subject.keywordAuthorGravitational search algorithm-
dc.subject.keywordAuthorMulti-modal-
dc.subject.keywordAuthorOptimization-
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