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An optimal critical level policy for inventory systems with two demand classes

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  • Karin T. Möllering
  • Ulrich W. Thonemann

Abstract

Traditional inventory systems treat all demands of a given item equally. This approach is optimal if the penalty costs of all customers are the same, but it is not optimal if the penalty costs are different for different customer classes. Then, demands of customers with high penalty costs must be filled before demands of customers with low penalty costs. A commonly used inventory policy for dealing with demands with different penalty costs is the critical level inventory policy. Under this policy demands with low penalty costs are filled as long as inventory is above a certain critical level. If the inventory reaches the critical level, only demands with high penalty costs are filled and demands with low penalty costs are backordered. In this article, we consider a critical level policy for a periodic review inventory system with two demand classes. Because traditional approaches cannot be used to find the optimal parameters of the policy, we use a multidimensional Markov chain to model the inventory system. We use a sample path approach to prove several properties of this inventory system. Although the cost function is not convex, we can build on these properties to develop an optimization approach that finds the optimal solution. We also present some numerical results. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008

Suggested Citation

  • Karin T. Möllering & Ulrich W. Thonemann, 2008. "An optimal critical level policy for inventory systems with two demand classes," Naval Research Logistics (NRL), John Wiley & Sons, vol. 55(7), pages 632-642, October.
  • Handle: RePEc:wly:navres:v:55:y:2008:i:7:p:632-642
    DOI: 10.1002/nav.20307
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    Cited by:

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    2. Wang, Yi & Zhang, Sheng Hao, 2021. "Optimal production and inventory rationing policies with selective-information sharing and two demand classes," European Journal of Operational Research, Elsevier, vol. 288(2), pages 394-407.
    3. Alfieri, Arianna & Pastore, Erica & Zotteri, Giulio, 2017. "Dynamic inventory rationing: How to allocate stock according to managerial priorities. An empirical study," International Journal of Production Economics, Elsevier, vol. 189(C), pages 14-29.
    4. Saha, Kushal & Bhattacharya, Subir, 2021. "‘Buy online and pick up in-store’: Implications for the store inventory," European Journal of Operational Research, Elsevier, vol. 294(3), pages 906-921.
    5. ElHafsi, Mohsen & Fang, Jianxin & Hamouda, Essia, 2021. "Optimal production and inventory control of multi-class mixed backorder and lost sales demand class models," European Journal of Operational Research, Elsevier, vol. 291(1), pages 147-161.

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