Recent Studies on Chicken Swarm Optimization algorithm: a review (2014–2018)

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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.accessioned2019-07-30T07:20:37Z
dc.date.available2019-07-30T07:20:37Z
dc.date.embargoinfo:eu-repo/date/embargoEnd/2020-05-23en_US
dc.date.issued2020-03-01en_US
dc.description.abstractSolving a complex optimization problem in a limited timeframe is a tedious task. Conventional gradient-based optimization algorithms have their limitations in solving complex problems such as unit commitment, microgrid planning, vehicle routing, feature selection, and community detection in social networks. In recent years population-based bio-inspired algorithms have demonstrated competitive performance on a wide range of optimization problems. Chicken Swarm Optimization Algorithm (CSO) is one of such bio-inspired meta-heuristic algorithms mimicking the behaviour of chicken swarm. It is reported in many literature that CSO outperforms a number of well-known meta-heuristics in a wide range of benchmark problems. This paper presents a review of various issues related to CSO like general biology, fundamentals, variants of CSO, performance of CSO, and applications of CSO.en
dc.description.versionPeer revieweden
dc.format.extent29
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationDeb, S, Gao, X Z, Tammi, K, Kalita, K & Mahanta, P 2020, ' Recent Studies on Chicken Swarm Optimization algorithm : a review (2014–2018) ', Artificial Intelligence Review, vol. 53, no. 3, pp. 1737-1765 . https://doi.org/10.1007/s10462-019-09718-3en
dc.identifier.doi10.1007/s10462-019-09718-3en_US
dc.identifier.issn0269-2821
dc.identifier.otherPURE UUID: d92cdfa7-1fa8-404a-a7de-7aa281347eeden_US
dc.identifier.otherPURE ITEMURL: https://research.aalto.fi/en/publications/d92cdfa7-1fa8-404a-a7de-7aa281347eeden_US
dc.identifier.otherPURE LINK: http://www.scopus.com/inward/record.url?scp=85066858369&partnerID=8YFLogxKen_US
dc.identifier.otherPURE FILEURL: https://research.aalto.fi/files/36987043/ENG_Deb_et_al_Recent_studies_on_chicken_swarm_Artificial_Intelligence_Review.pdfen_US
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/39510
dc.identifier.urnURN:NBN:fi:aalto-201907304565
dc.language.isoenen
dc.publisherSpringer Netherlands
dc.relation.ispartofseriesArtificial Intelligence Reviewen
dc.rightsopenAccessen
dc.subject.keywordApplicationsen_US
dc.subject.keywordChicken Swarm Optimization algorithmen_US
dc.subject.keywordNature inspired intelligenceen_US
dc.subject.keywordOptimization algorithmen_US
dc.subject.keywordReviewen_US
dc.titleRecent Studies on Chicken Swarm Optimization algorithm: a review (2014–2018)en
dc.typeA2 Katsausartikkeli tieteellisessä aikakauslehdessäfi
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