A New Teaching–Learning-based Chicken Swarm Optimization Algorithm

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dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.authorDeb, Sancharien_US
dc.contributor.authorGao, Xiao Zhien_US
dc.contributor.authorTammi, Karien_US
dc.contributor.authorKalita, Karunaen_US
dc.contributor.authorMahanta, Pinakeswaren_US
dc.contributor.departmentDepartment of Mechanical Engineeringen
dc.contributor.organizationIndian Institute of Technology Guwahatien_US
dc.contributor.organizationUniversity of Eastern Finlanden_US
dc.date.accessioned2019-11-07T12:01:51Z
dc.date.available2019-11-07T12:01:51Z
dc.date.embargoinfo:eu-repo/date/embargoEnd/2020-08-20en_US
dc.date.issued2019en_US
dc.description.abstractChicken Swarm Optimization (CSO) is a novel swarm intelligence-based algorithm known for its good performance on many benchmark functions as well as real-world optimization problems. However, it is observed that CSO sometimes gets trapped in local optima. This work proposes an improved version of the CSO algorithm with modified update equation of the roosters and a novel constraint-handling mechanism. Further, the work also proposes synergy of the improved version of CSO with Teaching–Learning-based Optimization (TLBO) algorithm. The proposed ICSOTLBO algorithm possesses the strengths of both CSO and TLBO. The efficacy of the proposed algorithm is tested on eight basic benchmark functions, fifteen computationally expensive benchmark functions as well as two real-world problems. Further, the performance of ICSOTLBO is also compared with a number of state-of-the-art algorithms. It is observed that the proposed algorithm performs better than or as good as many of the existing algorithms.en
dc.description.versionPeer revieweden
dc.format.extent19
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationDeb, S, Gao, X Z, Tammi, K, Kalita, K & Mahanta, P 2019, ' A New Teaching–Learning-based Chicken Swarm Optimization Algorithm ', Soft Computing . https://doi.org/10.1007/s00500-019-04280-0en
dc.identifier.doi10.1007/s00500-019-04280-0en_US
dc.identifier.issn1432-7643
dc.identifier.issn1433-7479
dc.identifier.otherPURE UUID: 273fe996-61f7-405d-9fa9-bfdd50b51c71en_US
dc.identifier.otherPURE ITEMURL: https://research.aalto.fi/en/publications/273fe996-61f7-405d-9fa9-bfdd50b51c71en_US
dc.identifier.otherPURE LINK: http://www.scopus.com/inward/record.url?scp=85071079732&partnerID=8YFLogxKen_US
dc.identifier.otherPURE FILEURL: https://research.aalto.fi/files/37756480/ENG_Deb_et_al_A_New_Teaching_Learning_Soft_Computing.pdfen_US
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/41038
dc.identifier.urnURN:NBN:fi:aalto-201911076043
dc.language.isoenen
dc.publisherSpringer Verlag
dc.relation.ispartofseriesSoft Computingen
dc.rightsopenAccessen
dc.subject.keywordAlgorithmen_US
dc.subject.keywordBenchmarken_US
dc.subject.keywordChicken Swarm Optimizationen_US
dc.subject.keywordFunctionen_US
dc.subject.keywordHybriden_US
dc.subject.keywordTeaching–Learning-based Optimizationen_US
dc.titleA New Teaching–Learning-based Chicken Swarm Optimization Algorithmen
dc.typeA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessäfi
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