Reliable multi period multi product supply chain design with facility disruption

This paper presents a strategic multi segment, multi period and multi-product supply chain management to meet reliable networks for handling disruptions strike. We present a mixedinteger programming model whose objective is to minimize the expected cost composed of probability and cost of occurrence in each scenario. The proposed model of this paper considers time value of money for each operation and transportation cost. We attempt to minimize expected costs by considering the levels of inventory, back-ordering, the available machine capacity and labor levels for each source, transportation capacity at each transshipment node and available warehouse space at each destination. The problem is generalized by taking into account backup supplier with reserved capacity and backup transshipment node that, which satisfies demands at higher price without disruption facility. We use a priority-based genetic algorithms encoding to solve the proposed problem under multi period and multi product conditions. The performance of the proposed model is examined using some instances.

[1]  Zuo-Jun Max Shen,et al.  The Reliable Facility Location Problem: Formulations, Heuristics, and Approximation Algorithms , 2011, INFORMS J. Comput..

[2]  Yanfeng Ouyang,et al.  A continuum approximation approach to reliable facility location design under correlated probabilistic disruptions , 2010 .

[3]  Lawrence V. Snyder,et al.  A random-key genetic algorithm for the generalized traveling salesman problem , 2006, Eur. J. Oper. Res..

[4]  Zvi Drezner,et al.  NETWORK DESIGN: SELECTION AND DESIGN OF LINKS AND FACILITY LOCATION , 2003 .

[5]  Germaine H. Saad,et al.  Managing Disruption Risks in Supply Chains , 2005 .

[6]  Andrew Lim,et al.  Reliable logistics networks design with facility disruptions , 2011 .

[7]  Christopher S. Tang Robust strategies for mitigating supply chain disruptions , 2006 .

[8]  Lawrence V. Snyder,et al.  Facility Location in Supply Chain Design , 2005 .

[9]  Zvi Drezner,et al.  An Efficient Genetic Algorithm for the p-Median Problem , 2003, Ann. Oper. Res..

[10]  Lawrence V. Snyder,et al.  Facility location under uncertainty: a review , 2006 .

[11]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[12]  Oded Berman,et al.  Facility Reliability Issues in Network p-Median Problems: Strategic Centralization and Co-Location Effects , 2007, Oper. Res..

[13]  D. Thurston,et al.  Modeling Robust and Reliable Supply Chains , 2003 .

[14]  Mark S. Daskin,et al.  A facility reliability problem: Formulation, properties, and algorithm , 2010 .

[15]  Yanfeng Ouyang,et al.  Reliable Facility Location Design Under the Risk of Disruptions , 2010, Oper. Res..

[16]  Lawrence V. Snyder,et al.  Reliability Models for Facility Location: The Expected Failure Cost Case , 2005, Transp. Sci..

[17]  Mitsuo Gen,et al.  Genetic algorithms and engineering optimization , 1999 .

[18]  Thomas L. Magnanti,et al.  Network Design and Transportation Planning: Models and Algorithms , 1984, Transp. Sci..

[19]  Zvi Drezner,et al.  Heuristic Solution Methods for Two Location Problems with Unreliable Facilities , 1987 .

[20]  Mary J. Meixell,et al.  Global supply chain design: A literature review and critique , 2005 .

[21]  Mark S. Daskin,et al.  Strategic facility location: A review , 1998, Eur. J. Oper. Res..

[22]  Mark S. Daskin,et al.  Planning for Disruptions in Supply Chain Networks , 2006 .

[23]  Mitsuo Gen,et al.  A genetic algorithm for two-stage transportation problem using priority-based encoding , 2006, OR Spectr..

[24]  Maria Paola Scaparra,et al.  Optimal Allocation of Protective Resources in Shortest-Path Networks , 2011, Transp. Sci..