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General Information
    • ISSN: 1793-8198
    • Frequency: Quarterly
    • DOI: 10.18178/IJMMM
    • Editor-in-Chief: Prof. K. M. Gupta, Prof. Ian McAndrew
    • Executive Editor: Ms. Cherry L. Chen
    • Abstracting/Indexing: EI (INSPEC, IET), Chemical Abstracts Services (CAS), Engineering & Technology Digital Library,  ProQuest, Crossref, Ulrich's Periodicals Directory, DOAJ, and Electronic Journals Library .
    • E-mail ijmmm@ejournal.net
Editor-in-chief
Prof. Ian McAndrew
Embry Riddle Aeronautical University, UK.
It is my honor to be the editor-in-chief of IJMMM. I will do my best to help develop this journal better.

IJMMM 2014 Vol.2(2): 139-145 ISSN: 1793-8198
DOI: 10.7763/IJMMM.2014.V2.116

A Stochastic Programming Approach to Supply Chain Disruptions Planning and Management

S. M. Ali and K. Nakade
Abstract—In this paper, we propose a stochastic programming approach to manage supply chain disruptions of an enterprise with an emphasis on demand and disruptions uncertainty. The supply chain considered here is multi-product, multi-agent in nature. However, the model considers purchasing cost, inventory cost and emergency ordering cost. Decisions such as ordering quantities in pre-disruptions and post-disruptions situation are taken into consideration. On the other hand, quality and delivery performance requirements are also included in the proposed analytical framework. We use Monte Carlo sampling approach for the purpose of sampling for a given probability distribution of stochastic parameters. In addition, we consider a disruptions planning case study and apply Benders decomposition (BD)/L-shaped algorithm to solve the model. The model is coded on GAMS 24.1.3 and run by CPLEX (12.5.1.0) and DECIS solver. We minimize total cost that includes first stage cost and second stage disruptions scenario cost. Several test instances with different disruptions scenarios are considered. We then compare the total costs under several disruptions scenarios. We hope that the model could be used as an effective tool to analyze and decide on supply chain disruptions planning and management of an enterprise thus it could contribute in continuity of manufacturing/business operations and therefore help in building a resilient supply chain.

Index Terms—Stochastic programming, supply chain disruptions, benders decomposition, Monte Carlo simulation.

The authors are with the Department of Architecture, Civil Engineering and Industrial Management Engineering in Nagoya Institute of Technology, Nagoya, Japan (e-mail: syed.mithun@gmail.com, nakade@nitech.ac.jp).

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Cite:A Stochastic Programming Approach to Supply Chain Disruptions Planning and Management, "S. M. Ali and K. Nakade," International Journal of Materials, Mechanics and Manufacturing vol. 2, no. 2, pp. 139-145, 2014.

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