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A bi-criteria indicator to assess supply chain network performance for critical needs under capacity and demand disruptions

  • Qiang, Patrick
  • Nagurney, Anna
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    In this paper, we develop a supply chain/logistics network model for critical needs in the case of disruptions. The objective is to minimize the total network costs, which are generalized costs that may include the monetary, risk, time, and social costs. The model assumes that disruptions may have an impact on both the network link capacities as well as on the product demands. Two different cases of disruption scenarios are considered. In the first case, we assume that the impacts of the disruptions are mild and that the demands can be met. In the second case, the demands cannot all be satisfied. For these two cases, we propose two individual performance indicators. We then construct a bi-criteria indicator to assess the supply chain network performance for critical needs. An algorithm is described which is applied to solve a spectrum of numerical examples in order to illustrate the new concepts.

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    Article provided by Elsevier in its journal Transportation Research Part A: Policy and Practice.

    Volume (Year): 46 (2012)
    Issue (Month): 5 ()
    Pages: 801-812

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    Handle: RePEc:eee:transa:v:46:y:2012:i:5:p:801-812
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    1. Anna Nagurney & Qiang Qiang, 2008. "An efficiency measure for dynamic networks modeled as evolutionary variational inequalities with application to the Internet and vulnerability analysis," Netnomics, Springer, vol. 9(1), pages 1-20, January.
    2. Zimmer, Kirstin, 2002. "Supply chain coordination with uncertain just-in-time delivery," International Journal of Production Economics, Elsevier, vol. 77(1), pages 1-15, May.
    3. Beamon, Benita M., 1998. "Supply chain design and analysis:: Models and methods," International Journal of Production Economics, Elsevier, vol. 55(3), pages 281-294, August.
    4. Lai, Kee-hung & Ngai, E. W. T. & Cheng, T. C. E., 2002. "Measures for evaluating supply chain performance in transport logistics," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 38(6), pages 439-456, November.
    5. Anna Nagurney & Min Yu & Qiang Qiang, 2011. "Supply chain network design for critical needs with outsourcing," Papers in Regional Science, Wiley Blackwell, vol. 90(1), pages 123-142, 03.
    6. Anna Nagurney & David Parkes & Patrizia Daniele, 2007. "The Internet, evolutionary variational inequalities, and the time-dependent Braess paradox," Computational Management Science, Springer, vol. 4(4), pages 355-375, October.
    7. Sheu, Jiuh-Biing, 2007. "An emergency logistics distribution approach for quick response to urgent relief demand in disasters," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(6), pages 687-709, November.
    8. Altay, Nezih & Green III, Walter G., 2006. "OR/MS research in disaster operations management," European Journal of Operational Research, Elsevier, vol. 175(1), pages 475-493, November.
    9. Nagurney, Anna, 2009. "A system-optimization perspective for supply chain network integration: The horizontal merger case," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 45(1), pages 1-15, January.
    10. Michael Taylor & Somenahalli Sekhar & Glen D'Este, 2006. "Application of Accessibility Based Methods for Vulnerability Analysis of Strategic Road Networks," Networks and Spatial Economics, Springer, vol. 6(3), pages 267-291, September.
    11. Wilson, Martha C., 2007. "The impact of transportation disruptions on supply chain performance," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(4), pages 295-320, July.
    12. Hau Lee & Seungjin Whang, 1999. "Decentralized Multi-Echelon Supply Chains: Incentives and Information," Management Science, INFORMS, vol. 45(5), pages 633-640, May.
    13. Nagurney, Anna, 2006. "On the relationship between supply chain and transportation network equilibria: A supernetwork equivalence with computations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 42(4), pages 293-316, July.
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