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Approximate dynamic programming methods for an inventory allocation problem under uncertainty

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  • Huseyin Topaloglu
  • Sumit Kunnumkal

Abstract

We propose two approximate dynamic programming methods to optimize the distribution operations of a company manufacturing a certain product at multiple production plants and shipping it to different customer locations for sale. We begin by formulating the problem as a dynamic program. Our first approximate dynamic programming method uses a linear approximation of the value function and computes the parameters of this approximation by using the linear programming representation of the dynamic program. Our second method relaxes the constraints that link the decisions for different production plants. Consequently, the dynamic program decomposes by the production plants. Computational experiments show that the proposed methods are computationally attractive, and in particular, the second method performs significantly better than standard benchmarks. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006

Suggested Citation

  • Huseyin Topaloglu & Sumit Kunnumkal, 2006. "Approximate dynamic programming methods for an inventory allocation problem under uncertainty," Naval Research Logistics (NRL), John Wiley & Sons, vol. 53(8), pages 822-841, December.
    • Handle: RePEc:wly:navres:v:53:y:2006:i:8:p:822-841
    DOI: 10.1002/nav.20164
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    References listed on IDEAS

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    Cited by:

    1. Amin Khademi & Burak Eksioglu, 2018. "Spare Parts Inventory Management with Substitution-Dependent Reliability," INFORMS Journal on Computing, INFORMS, vol. 30(3), pages 507-521, August.
    2. Zhou, Jianheng & Luo, Yao, 2023. "Bayes information updating and multiperiod supply chain screening," International Journal of Production Economics, Elsevier, vol. 256(C).
    3. Mochen Yang & Gediminas Adomavicius & Alok Gupta, 2019. "Efficient Computational Strategies for Dynamic Inventory Liquidation," Information Systems Research, INFORMS, vol. 30(2), pages 595-615, June.
    4. Frank Schneider & Ulrich W. Thonemann & Diego Klabjan, 2018. "Optimization of Battery Charging and Purchasing at Electric Vehicle Battery Swap Stations," Transportation Science, INFORMS, vol. 52(5), pages 1211-1234, October.
    5. Sumit Kunnumkal & Huseyin Topaloglu, 2008. "A duality‐based relaxation and decomposition approach for inventory distribution systems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 55(7), pages 612-631, October.
    6. Qihang Lin & Selvaprabu Nadarajah & Negar Soheili, 2020. "Revisiting Approximate Linear Programming: Constraint-Violation Learning with Applications to Inventory Control and Energy Storage," Management Science, INFORMS, vol. 66(4), pages 1544-1562, April.
    7. Charles I. Nkeki, 2013. "Dynamic Optimization Technique for Distribution of Goods with Stochastic Shortages," Journal of Optimization, Hindawi, vol. 2013, pages 1-12, December.

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