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Scenario-based Supply Chain Network risk modeling

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  • Klibi, Walid
  • Martel, Alain

Abstract

This paper provides a risk modeling approach to facilitate the evaluation and the design of Supply Chain Networks (SCNs) operating under uncertainty. The usefulness of the approach is demonstrated with two realistic case studies. Three event types are defined to describe plausible future SCN environments: random, hazardous and deeply uncertain events. A three-phase hazard modeling approach is also proposed. It involves a characterization of SCN hazards in terms of multihazards, vulnerability sources and exposure levels; the estimation of incident arrival, intensity and duration processes; and the assessment of SCN hit consequences in terms of damage and time to recovery. Based on these descriptive models, a Monte Carlo approach is then proposed to generate plausible future scenarios. The two cases studied illustrate the key aspects of the approach, and how it can be used to obtain resilient SCNs under disruptions.

Suggested Citation

  • Klibi, Walid & Martel, Alain, 2012. "Scenario-based Supply Chain Network risk modeling," European Journal of Operational Research, Elsevier, vol. 223(3), pages 644-658.
    • Handle: RePEc:eee:ejores:v:223:y:2012:i:3:p:644-658
    DOI: 10.1016/j.ejor.2012.06.027
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    References listed on IDEAS

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    1. Tang, Christopher S., 2006. "Perspectives in supply chain risk management," International Journal of Production Economics, Elsevier, vol. 103(2), pages 451-488, October.
    2. Arnd Huchzermeier & Morris A. Cohen, 1996. "Valuing Operational Flexibility Under Exchange Rate Risk," Operations Research, INFORMS, vol. 44(1), pages 100-113, February.
    3. Bilsel, R. Ufuk & Ravindran, A., 2011. "A multiobjective chance constrained programming model for supplier selection under uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 45(8), pages 1284-1300, September.
    4. Azaron, A. & Brown, K.N. & Tarim, S.A. & Modarres, M., 2008. "A multi-objective stochastic programming approach for supply chain design considering risk," International Journal of Production Economics, Elsevier, vol. 116(1), pages 129-138, November.
    5. Robert J. Lempert & David G. Groves & Steven W. Popper & Steve C. Bankes, 2006. "A General, Analytic Method for Generating Robust Strategies and Narrative Scenarios," Management Science, INFORMS, vol. 52(4), pages 514-528, April.
    6. Jitka Dupačová & Giorgio Consigli & Stein Wallace, 2000. "Scenarios for Multistage Stochastic Programs," Annals of Operations Research, Springer, vol. 100(1), pages 25-53, December.
    7. Kevin B. Hendricks & Vinod R. Singhal, 2005. "Association Between Supply Chain Glitches and Operating Performance," Management Science, INFORMS, vol. 51(5), pages 695-711, May.
    8. Shabbir Ahmed & Nikolaos V. Sahinidis, 2003. "An Approximation Scheme for Stochastic Integer Programs Arising in Capacity Expansion," Operations Research, INFORMS, vol. 51(3), pages 461-471, June.
    9. Klibi, Walid & Martel, Alain & Guitouni, Adel, 2010. "The design of robust value-creating supply chain networks: A critical review," European Journal of Operational Research, Elsevier, vol. 203(2), pages 283-293, June.
    10. Yossi Sheffi, 2005. "The Resilient Enterprise: Overcoming Vulnerability for Competitive Advantage," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262693496, April.
    11. Santoso, Tjendera & Ahmed, Shabbir & Goetschalckx, Marc & Shapiro, Alexander, 2005. "A stochastic programming approach for supply chain network design under uncertainty," European Journal of Operational Research, Elsevier, vol. 167(1), pages 96-115, November.
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