A Novel Numerical Approach to the MCLP Based Resilent Supply Chain Optimization

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dc.contributor.affiliationAzhmyakov, V., Departamento de Ciencias Basicas, Universidad de Medellin, Medellin, Colombiaspa
dc.contributor.affiliationFacultad de Ingenieria Mecanica y Electrica, Universidad Autonoma de Coahuila, Torreon, Mexicospa
dc.contributor.affiliationDepartment of Computer Science, Universität der Bundeswehr München, München, Germanyspa
dc.contributor.affiliationPickl, S., Department of Computer Science, Universität der Bundeswehr München, München, Germanyspa
dc.contributor.authorAzhmyakov V.
dc.contributor.authorFernández-Gutiérrez J.P.
dc.contributor.authorGadi S.K.
dc.contributor.authorPickl S.
dc.date.accessioned2017-12-19T19:36:52Z
dc.date.available2017-12-19T19:36:52Z
dc.date.issued2016
dc.description.abstractThis paper deals with the Maximal Covering Location Problem (MCLP) for Supply Chain optimization in the presence of incomplete information. A specific linear-integer structure of a generic mathematical model for Resilient Supply Chain Management System (RSCMS) makes it possible to reduce the originally given MCLP to two auxiliary optimization Knapsack-type problems. The equivalent transformation (separation) we propose provides a useful tool for an effective numerical treatment of the original MCLP and reduces the complexity of algorithms. The computational methodology we follow involves a specific Lagrange relaxation procedure. We give a rigorous formal analysis of the resulting algorithm and apply it to a practically oriented example of an optimal RSCMS design. © 2016eng
dc.identifier.doi10.1016/j.ifacol.2016.12.175
dc.identifier.instnameinstname:Universidad de Medellínspa
dc.identifier.issn24058963
dc.identifier.reponamereponame:Repositorio Institucional Universidad de Medellínspa
dc.identifier.urihttp://hdl.handle.net/11407/4379
dc.language.isoeng
dc.publisherElsevier B.V.spa
dc.publisher.facultyFacultad de Ciencias Básicasspa
dc.relation.ispartofIFAC-PapersOnLinespa
dc.relation.ispartofIFAC-PapersOnLine Volume 49, Issue 31, 2016, Pages 137-142spa
dc.relation.isversionofhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85012868634&doi=10.1016%2fj.ifacol.2016.12.175&partnerID=40&md5=26ac509f85a752096da4a6e849f29c78
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dc.rights.accessrightsinfo:eu-repo/semantics/restrictedAccess
dc.sourceScopusspa
dc.subject.proposalComputational complexityeng
dc.subject.proposalInteger programmingeng
dc.subject.proposalSupply chain managementeng
dc.subject.proposalComplexity of algorithmeng
dc.subject.proposalComputational methodologyeng
dc.subject.proposalEquivalent transformationseng
dc.subject.proposalIncomplete informationeng
dc.subject.proposalMaximal covering location problems (MCLP)eng
dc.subject.proposalNumerical approacheseng
dc.subject.proposalSupply chain management systemeng
dc.subject.proposalSupply chain optimizationeng
dc.subject.proposalOptimizationeng
dc.titleA Novel Numerical Approach to the MCLP Based Resilent Supply Chain Optimizationspa
dc.typeArticle
dc.type.driverinfo:eu-repo/semantics/article
dc.type.versioninfo:eu-repo/semantics/publishedVersion

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