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Replenishment Strategies for Distribution Systems Under Advance Demand Information

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  • Özalp Özer

    (Department of Management Science and Engineering, Stanford University, Stanford, California 94305)

Abstract

Customers with positive demand lead times place orders in advance of their needs. A portfolio of customers with different demand lead times gives rise to what we call advance demand information. We develop effective inventory policies for a distribution system to account for this information. In particular, we study a centralized system with one warehouse serving multiple retailers under advance demand information. The inventory manager replenishes the warehouse from an outside supplier. Units arriving to the warehouse are allocated to the retailers. To control this system, we develop a lower bound and proposed a close-to-optimal heuristic for which the optimality gap is on average 1.92%. We also provide a closed-form solution to approximate the system-wide inventory level. Using this explicit solution, the model and the heuristic, we investigate (1) the benefit of advance demand information, and its impact on allocation decisions, (2) the joint role of risk pooling and advance demand information, and (3) the system performance with respect to supplier and retailer lead times. We illustrate how advance demand information can be a substitute for lead times and inventory, and how it enhances the outcome of delayed differentiation.

Suggested Citation

  • Özalp Özer, 2003. "Replenishment Strategies for Distribution Systems Under Advance Demand Information," Management Science, INFORMS, vol. 49(3), pages 255-272, March.
    • Handle: RePEc:inm:ormnsc:v:49:y:2003:i:3:p:255-272
    DOI: 10.1287/mnsc.49.3.255.12738
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    References listed on IDEAS

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