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A Novel Numerical Approach to the MCLP Based Resilent Supply Chain Optimization
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.accessioned | 2017-12-19T19:36:52Z | |
dc.date.available | 2017-12-19T19:36:52Z | |
dc.date.created | 2016 | |
dc.identifier.issn | 24058963 | |
dc.identifier.uri | http://hdl.handle.net/11407/4379 | |
dc.description.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 | eng |
dc.language.iso | eng | |
dc.publisher | Elsevier B.V. | 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.title | A Novel Numerical Approach to the MCLP Based Resilent Supply Chain Optimization | spa |
dc.type | Article | eng |
dc.rights.accessrights | info:eu-repo/semantics/restrictedAccess | |
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 | |
dc.subject.keyword | Computational complexity | eng |
dc.subject.keyword | Integer programming | eng |
dc.subject.keyword | Supply chain management | eng |
dc.subject.keyword | Complexity of algorithm | eng |
dc.subject.keyword | Computational methodology | eng |
dc.subject.keyword | Equivalent transformations | eng |
dc.subject.keyword | Incomplete information | eng |
dc.subject.keyword | Maximal covering location problems (MCLP) | eng |
dc.subject.keyword | Numerical approaches | eng |
dc.subject.keyword | Supply chain management system | eng |
dc.subject.keyword | Supply chain optimization | eng |
dc.subject.keyword | Optimization | eng |
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 | eng |
dc.creator.affiliation | Departamento de Ciencias Basicas, Universidad de Medellin, Medellin, Colombia | spa |
dc.creator.affiliation | Facultad de Ingenieria Mecanica y Electrica, Universidad Autonoma de Coahuila, Torreon, Mexico | spa |
dc.creator.affiliation | Department of Computer Science, Universität der Bundeswehr München, München, Germany | spa |
dc.relation.ispartofes | IFAC-PapersOnLine | spa |
dc.relation.ispartofes | IFAC-PapersOnLine Volume 49, Issue 31, 2016, Pages 137-142 | spa |
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dc.type.version | info:eu-repo/semantics/publishedVersion | |
dc.type.driver | info:eu-repo/semantics/article | |
dc.identifier.reponame | reponame:Repositorio Institucional Universidad de Medellín | spa |
dc.identifier.instname | instname:Universidad de Medellín | spa |
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