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

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Date
2016
Author
Azhmyakov V.
Fernández-Gutiérrez J.P.
Gadi S.K.
Pickl S.
Departamento de Ciencias Basicas, Universidad de Medellin, Medellin, Colombia
Facultad de Ingenieria Mecanica y Electrica, Universidad Autonoma de Coahuila, Torreon, Mexico
Department of Computer Science, Universität der Bundeswehr München, München, Germany

Citación

       
TY - GEN T1 - A Novel Numerical Approach to the MCLP Based Resilent Supply Chain Optimization AU - Azhmyakov V. AU - Fernández-Gutiérrez J.P. AU - Gadi S.K. AU - Pickl S. Y1 - 2016 UR - http://hdl.handle.net/11407/4379 PB - Elsevier B.V. AB - ER - @misc{11407_4379, author = {Azhmyakov V. and Fernández-Gutiérrez J.P. and Gadi S.K. and Pickl S.}, title = {A Novel Numerical Approach to the MCLP Based Resilent Supply Chain Optimization}, year = {2016}, abstract = {}, url = {http://hdl.handle.net/11407/4379} }RT Generic T1 A Novel Numerical Approach to the MCLP Based Resilent Supply Chain Optimization A1 Azhmyakov V. A1 Fernández-Gutiérrez J.P. A1 Gadi S.K. A1 Pickl S. YR 2016 LK http://hdl.handle.net/11407/4379 PB Elsevier B.V. AB OL Spanish (121)
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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
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http://hdl.handle.net/11407/4379
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