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Optimal Stock Allocation for a Capacitated Supply System

Author

Listed:
  • Francis de Véricourt

    (Fuqua School of Business, Duke University, Durham, North Carolina 27708)

  • Fikri Karaesmen

    (Department of Industrial Engineering, Koç University, 80910 Sariyer-Istanbul, Turkey)

  • Yves Dallery

    (Laboratoire Génie Industriel, Ecole Centrale Paris, Grande Voie des Vignes, 92295 Châtenay-Malabry Cedex, France)

Abstract

We consider a capacitated supply system that produces a single item that is demanded by several classes of customers. Each customer class may have a different backorder cost, so stock allocation arises as a key decision problem. We model the supply system as a multi customer make-to-stock queue. Using dynamic programming, we show that the optimal allocation policy has a simple and intuitive structure. In addition, we present an efficient algorithm to compute the parameters of this optimal allocation policy. Finally, for a typical supply chain design problem, we illustrate that ignoring the stock allocation dimension---a frequently encountered simplifying assumption---can lead to incorrect managerial decisions.

Suggested Citation

  • Francis de Véricourt & Fikri Karaesmen & Yves Dallery, 2002. "Optimal Stock Allocation for a Capacitated Supply System," Management Science, INFORMS, vol. 48(11), pages 1486-1501, November.
    • Handle: RePEc:inm:ormnsc:v:48:y:2002:i:11:p:1486-1501
    DOI: 10.1287/mnsc.48.11.1486.263
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    References listed on IDEAS

    as
    1. Francis De Vericourt & Fikri Karaesmen & Yves Dallery, 2000. "Dynamic Scheduling in a Make-to-Stock System: A Partial Characterization of Optimal Policies," Operations Research, INFORMS, vol. 48(5), pages 811-819, October.
    2. Gary D. Eppen, 1979. "Note--Effects of Centralization on Expected Costs in a Multi-Location Newsboy Problem," Management Science, INFORMS, vol. 25(5), pages 498-501, May.
    3. Morris A. Cohen & Paul R. Kleindorfer & Hau L. Lee, 1988. "Service Constrained (s, S) Inventory Systems with Priority Demand Classes and Lost Sales," Management Science, INFORMS, vol. 34(4), pages 482-499, April.
    4. Leroy B. Schwarz, 1989. "A Model for Assessing the Value of Warehouse Risk-Pooling: Risk-Pooling Over Outside-Supplier Leadtimes," Management Science, INFORMS, vol. 35(7), pages 828-842, July.
    5. Donald M. Topkis, 1968. "Optimal Ordering and Rationing Policies in a Nonstationary Dynamic Inventory Model with n Demand Classes," Management Science, INFORMS, vol. 15(3), pages 160-176, November.
    6. Steven Nahmias & W. Steven Demmy, 1981. "Operating Characteristics of an Inventory System with Rationing," Management Science, INFORMS, vol. 27(11), pages 1236-1245, November.
    7. Albert Y. Ha, 1997. "Inventory Rationing in a Make-to-Stock Production System with Several Demand Classes and Lost Sales," Management Science, INFORMS, vol. 43(8), pages 1093-1103, August.
    8. Francis de Véricourt & Fikri Karaesmen & Yves Dallery, 2001. "Assessing the Benefits of Different Stock-Allocation Policies for a Make-to-Stock Production System," Manufacturing & Service Operations Management, INFORMS, vol. 3(2), pages 105-121, December.
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