Hybrid evolutionary algorithm for the Capacitated Centered Clustering Problem

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dc.contributor.authorChaves, Antonio Augusto [UNESP]
dc.contributor.authorNogueira Lorena, Luiz Antonio
dc.contributor.institutionInstituto Nacional de Pesquisas Espaciais (INPE)
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2014-05-20T13:28:14Z
dc.date.available2014-05-20T13:28:14Z
dc.date.issued2011-05-01
dc.description.abstractThe Capacitated Centered Clustering Problem (CCCP) consists of defining a set of p groups with minimum dissimilarity on a network with n points. Demand values are associated with each point and each group has a demand capacity. The problem is well known to be NP-hard and has many practical applications. In this paper, the hybrid method Clustering Search (CS) is implemented to solve the CCCP. This method identifies promising regions of the search space by generating solutions with a metaheuristic, such as Genetic Algorithm, and clustering them into clusters that are then explored further with local search heuristics. Computational results considering instances available in the literature are presented to demonstrate the efficacy of CS. (C) 2010 Elsevier Ltd. All rights reserved.en
dc.description.affiliationNatl Inst Space Res, Lab Comp & Appl Math, Sao Jose Dos Campos, Brazil
dc.description.affiliationSão Paulo State Univ, Dept Math, Guaratingueta, Brazil
dc.description.affiliationUnespSão Paulo State Univ, Dept Math, Guaratingueta, Brazil
dc.format.extent5013-5018
dc.identifierhttp://dx.doi.org/10.1016/j.eswa.2010.09.149
dc.identifier.citationExpert Systems With Applications. Oxford: Pergamon-Elsevier B.V. Ltd, v. 38, n. 5, p. 5013-5018, 2011.
dc.identifier.doi10.1016/j.eswa.2010.09.149
dc.identifier.issn0957-4174
dc.identifier.urihttp://hdl.handle.net/11449/9379
dc.identifier.wosWOS:000287419900040
dc.language.isoeng
dc.publisherPergamon-Elsevier B.V. Ltd
dc.relation.ispartofExpert Systems with Applications
dc.relation.ispartofjcr3.768
dc.relation.ispartofsjr1,271
dc.rights.accessRightsAcesso restrito
dc.sourceWeb of Science
dc.subjectClustering problemsen
dc.subjectClustering search algorithmen
dc.subjectGenetic Algorithmen
dc.subjectMetaheuristicsen
dc.titleHybrid evolutionary algorithm for the Capacitated Centered Clustering Problemen
dc.typeArtigo
dcterms.licensehttp://www.elsevier.com/about/open-access/open-access-policies/article-posting-policy
dcterms.rightsHolderPergamon-Elsevier B.V. Ltd
unesp.campusUniversidade Estadual Paulista (Unesp), Faculdade de Engenharia, Guaratinguetápt

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