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

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dc.creator Azhmyakov V. spa
dc.creator Fernández-Gutiérrez J.P. spa
dc.creator Gadi S.K. spa
dc.creator Pickl S. spa
dc.date 2016 spa
dc.date.accessioned 2017-12-19T19:36:52Z
dc.date.available 2017-12-19T19:36:52Z
dc.identifier.issn 24058963 spa
dc.identifier.uri http://hdl.handle.net/11407/4379
dc.language.iso Eng spa
dc.publisher Elsevier B.V. spa
dc.relation.ispartof IFAC-PapersOnLine spa
dc.relation.ispartof IFAC-PapersOnLine Volume 49, Issue 31, 2016, Pages 137-142 spa
dc.relation.isversionof https://www.scopus.com/inward/record.uri?eid=2-s2.0-85012868634&doi=10.1016%2fj.ifacol.2016.12.175&partnerID=40&md5=26ac509f85a752096da4a6e849f29c78 spa
dc.source Scopus spa
dc.source reponame:Repositorio Institucional spa
dc.source instname:Universidad de Medellín spa
dc.title A Novel Numerical Approach to the MCLP Based Resilent Supply Chain Optimization spa
dc.type Article spa
dc.type info:eu-repo/semantics/publishedVersion spa
dc.type info:eu-repo/semantics/article spa
dc.rights.accessRights restrictedAccess spa
dc.contributor.affiliation Azhmyakov, V., Departamento de Ciencias Basicas, Universidad de Medellin, Medellin, Colombia spa
dc.contributor.affiliation Fernández-Gutiérrez, J.P., Departamento de Ciencias Basicas, Universidad de Medellin, Medellin, Colombia spa
dc.contributor.affiliation Gadi, S.K., Facultad de Ingenieria Mecanica y Electrica, Universidad Autonoma de Coahuila, Torreon, Mexico spa
dc.contributor.affiliation Pickl, S., Department of Computer Science, Universität der Bundeswehr München, München, Germany spa
dc.identifier.doi 10.1016/j.ifacol.2016.12.175 spa
dc.subject.keyword Computational complexity spa
dc.subject.keyword Integer programming spa
dc.subject.keyword Supply chain management spa
dc.subject.keyword Complexity of algorithm spa
dc.subject.keyword Computational methodology spa
dc.subject.keyword Equivalent transformations spa
dc.subject.keyword Incomplete information spa
dc.subject.keyword Maximal covering location problems (MCLP) spa
dc.subject.keyword Numerical approaches spa
dc.subject.keyword Supply chain management system spa
dc.subject.keyword Supply chain optimization spa
dc.subject.keyword Optimization spa
dc.publisher.faculty Facultad de Ciencias Básicas spa
dc.abstract This 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. © 2016 spa
dc.affiliation Departamento de Ciencias Basicas, Universidad de Medellin, Medellin, Colombia spa
dc.affiliation Facultad de Ingenieria Mecanica y Electrica, Universidad Autonoma de Coahuila, Torreon, Mexico spa
dc.affiliation Department of Computer Science, Universität der Bundeswehr München, München, Germany spa
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