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

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

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
URI: http://hdl.handle.net/11407/4379

Resumen:

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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