A New Chaotic Starling Particle Swarm Optimization Algorithm for Clustering Problems

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dc.contributor.authorWang, Lin
dc.contributor.authorLiu, Xiyu
dc.contributor.authorSun, Minghe
dc.contributor.authorQu, Jianhua
dc.contributor.authorWei, Yanmeng
dc.creator.orcidhttps://orcid.org/0000-0001-8503-9761en_US
dc.date.accessioned2023-04-03T16:51:37Z
dc.date.available2023-04-03T16:51:37Z
dc.date.issued2018-08-19
dc.description.abstractA new method using collective responses of starling birds is developed to enhance the global search performance of standard particle swarm optimization (PSO). The method is named chaotic starling particle swarm optimization (CSPSO). In CSPSO, the inertia weight is adjusted using a nonlinear decreasing approach and the acceleration coefficients are adjusted using a chaotic logistic mapping strategy to avoid prematurity of the search process. A dynamic disturbance term (DDT) is used in velocity updating to enhance convergence of the algorithm. A local search method inspired by the behavior of starling birds utilizing the information of the nearest neighbors is used to determine a new collective position and a new collective velocity for selected particles. Two particle selection methods, Euclidean distance and fitness function, are adopted to ensure the overall convergence of the search process. Experimental results on benchmark function optimization and classic clustering problems verified the effectiveness of this proposed CSPSO algorithm.en_US
dc.description.departmentManagement Science and Statisticsen_US
dc.description.sponsorshipNational Natural Science Foundation of China; Humanities and Social Science Research Fund of the Ministry of Education of China; Shandong Social Science Foundation of Chinaen_US
dc.identifier.citationWang, L., Liu, X., Sun, M., Qu, J., & Wei, Y. (2018). A New Chaotic Starling Particle Swarm Optimization Algorithm for Clustering Problems. Mathematical Problems in Engineering, 2018, 8250480. doi:10.1155/2018/8250480en_US
dc.identifier.issn1563-5147
dc.identifier.otherhttps://doi.org/10.1155/2018/8250480
dc.identifier.urihttps://hdl.handle.net/20.500.12588/1809
dc.language.isoen_USen_US
dc.publisherHindawien_US
dc.relation.ispartofseriesMathematical Problems in Engineering, 2018;
dc.rightsAttribution 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/us/*
dc.titleA New Chaotic Starling Particle Swarm Optimization Algorithm for Clustering Problemsen_US
dc.typeArticleen_US

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