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A dynamic competitive swarm optimizer based-on entropy for large scale optimization

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dc.contributor.authorZhang, Wen-Xiao-
dc.contributor.authorChen, Wei-Neng-
dc.contributor.authorZhang, Jun-
dc.date.accessioned2023-12-12T12:30:52Z-
dc.date.available2023-12-12T12:30:52Z-
dc.date.issued2016-04-
dc.identifier.urihttps://scholarworks.bwise.kr/erica/handle/2021.sw.erica/116341-
dc.description.abstractIn this paper, a dynamic competitive swarm optimizer (DCSO) based on population entropy is proposed. The new algorithm is derived from the competitive swarm optimizer (CSO). The new algorithm uses population entropy to make a quantitative description about the diversity of population, and to divide the population into two sub-groups dynamically. During the early stage of the execution process, to speed up convergence of the algorithm, the sub-group with better fitness will have a small size, and worse large sub-group will learn from small one. During the late stage of the execution process, to keep the diversity of the population, the sub-group with better fitness will have a large size, and small worse sub-group will learn from large group. The proposed DCSO is evaluated on CEC'08 benchmark functions on large scale global optimization. The simulation results of the example indicate that the new algorithm has better and faster convergence speed than CSO. © 2016 IEEE.-
dc.format.extent7-
dc.language영어-
dc.language.isoENG-
dc.publisherInstitute of Electrical and Electronics Engineers Inc.-
dc.titleA dynamic competitive swarm optimizer based-on entropy for large scale optimization-
dc.typeArticle-
dc.publisher.location미국-
dc.identifier.doi10.1109/ICACI.2016.7449853-
dc.identifier.scopusid2-s2.0-84966508542-
dc.identifier.wosidProceedings Paper-
dc.identifier.bibliographicCitation2016 Eighth International Conference on Advanced Computational Intelligence (ICACI), pp 365 - 371-
dc.citation.title2016 Eighth International Conference on Advanced Computational Intelligence (ICACI)-
dc.citation.startPage365-
dc.citation.endPage371-
dc.type.docTypeConference paper-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClasssci-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalWebOfScienceCategoryComputer Science, Artificial Intelligence-
dc.relation.journalWebOfScienceCategoryEngineering, Electrical & Electronic-
dc.subject.keywordPlusCOOPERATIVE COEVOLUTION-
dc.subject.keywordAuthorcompetitive swarm optimizer-
dc.subject.keywordAuthorlarge scale optimization-
dc.subject.keywordAuthorpairwise competition-
dc.subject.keywordAuthorpopulation entropy-
dc.subject.keywordAuthorsub-group-
dc.identifier.urlhttps://ieeexplore.ieee.org/document/7449853?arnumber=7449853&SID=EBSCO:edseee-
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ERICA 공학대학 (SCHOOL OF ELECTRICAL ENGINEERING)
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