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dc.creatorAzhmyakov V.spa
dc.creatorFernandez-Gutierrez J.P.spa
dc.creatorPickl S.spa
dc.date.accessioned2017-12-19T19:36:45Z
dc.date.available2017-12-19T19:36:45Z
dc.date.created2017
dc.identifier.issn11268042
dc.identifier.urihttp://hdl.handle.net/11407/4286
dc.description.abstractOur paper discusses a novel computational approach to the extended Maximal Covering Location Problem (MCLP). We consider a fuzzy-type formulation of the generic MCLP and develop the necessary theoretical and numerical aspects of the proposed Separation Method (SM). A speciffic structure of the originally given MCLP makes it possible to reduce it to two auxiliary Knapsack-type problems. The equivalent separation we propose reduces essentially the complexity of the resulting computational algorithms. This algorithm also incorporates a conventional relaxation technique and the scalarizing method applied to an auxiliary multiobjective optimization problem. The proposed solution methodology is next applied to Supply Chain optimization in the presence of incomplete information. We study two illustrative examples and give a rigorous analysis of the obtained results.eng
dc.language.isoeng
dc.publisherForum-Editrice Universitaria Udinese SRLspa
dc.relation.isversionofhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85029392455&partnerID=40&md5=6a4351f1e2812f81178c421a301bbbbbspa
dc.sourceScopusspa
dc.titleA separation method for maximal covering location problems with fuzzy parametersspa
dc.typeArticleeng
dc.rights.accessrightsinfo:eu-repo/semantics/restrictedAccess
dc.contributor.affiliationAzhmyakov, V., Department of Basic Sciences, Universidad de Medellin, Medellin, Colombiaspa
dc.contributor.affiliationFernandez-Gutierrez, J.P., Department of Basic Sciences, Universidad de Medellin, Medellin, Colombiaspa
dc.contributor.affiliationPickl, S., Institut fur Theoretische Informatik, Mathematik und Operations Research, Fakultat fur Informatik, Universitat der Bundeswehr Munchen, Munchen, Germanyspa
dc.subject.keywordInteger optimizationeng
dc.subject.keywordMCLPeng
dc.subject.keywordNumerical optimizationeng
dc.subject.keywordInteger programmingeng
dc.subject.keywordMultiobjective optimizationeng
dc.subject.keywordNumerical methodseng
dc.subject.keywordSeparationeng
dc.subject.keywordSite selectioneng
dc.subject.keywordSupply chainseng
dc.subject.keywordComputational algorithmeng
dc.subject.keywordInteger optimizationeng
dc.subject.keywordMaximal covering location problemseng
dc.subject.keywordMaximal covering location problems (MCLP)eng
dc.subject.keywordMCLPeng
dc.subject.keywordMulti-objective optimization problemeng
dc.subject.keywordNumerical optimizationseng
dc.subject.keywordSupply chain optimizationeng
dc.subject.keywordOptimizationeng
dc.publisher.facultyFacultad de Ciencias Básicasspa
dc.abstractOur paper discusses a novel computational approach to the extended Maximal Covering Location Problem (MCLP). We consider a fuzzy-type formulation of the generic MCLP and develop the necessary theoretical and numerical aspects of the proposed Separation Method (SM). A speciffic structure of the originally given MCLP makes it possible to reduce it to two auxiliary Knapsack-type problems. The equivalent separation we propose reduces essentially the complexity of the resulting computational algorithms. This algorithm also incorporates a conventional relaxation technique and the scalarizing method applied to an auxiliary multiobjective optimization problem. The proposed solution methodology is next applied to Supply Chain optimization in the presence of incomplete information. We study two illustrative examples and give a rigorous analysis of the obtained results.eng
dc.creator.affiliationDepartment of Basic Sciences, Universidad de Medellin, Medellin, Colombiaspa
dc.creator.affiliationInstitut fur Theoretische Informatik, Mathematik und Operations Research, Fakultat fur Informatik, Universitat der Bundeswehr Munchen, Munchen, Germanyspa
dc.relation.ispartofesItalian Journal of Pure and Applied Mathematicsspa
dc.relation.ispartofesItalian Journal of Pure and Applied Mathematics Issue 38, July 2017, Pages 653-670spa
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dc.type.versioninfo:eu-repo/semantics/publishedVersion
dc.type.driverinfo:eu-repo/semantics/article
dc.identifier.reponamereponame:Repositorio Institucional Universidad de Medellínspa
dc.identifier.instnameinstname:Universidad de Medellínspa


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