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The Dynamic Inventory Problem with Unknown Demand Distribution


  • Donald L. Iglehart

    (Cornell University)


In this paper we consider the dynamic inventory problem in which the demand distribution possesses a density belonging to either the exponential or range family of densities and having an unknown parameter. An a priori density is chosen for the unknown parameter. Using a Bayesian estimation scheme, inequalities are obtained for the optimal purchase policies as the amount of demand information varies. In addition, asymptotic expansions for the optimal policies are found as the number of observations of the demand becomes large. This paper extends the results of Scarf, [8].

Suggested Citation

  • Donald L. Iglehart, 1964. "The Dynamic Inventory Problem with Unknown Demand Distribution," Management Science, INFORMS, vol. 10(3), pages 429-440, April.
  • Handle: RePEc:inm:ormnsc:v:10:y:1964:i:3:p:429-440

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    Cited by:

    1. Berk, Emre & Gurler, Ulku & Levine, Richard A., 2007. "Bayesian demand updating in the lost sales newsvendor problem: A two-moment approximation," European Journal of Operational Research, Elsevier, vol. 182(1), pages 256-281, October.
    2. Larson, C. Erik & Olson, Lars J. & Sharma, Sunil, 2001. "Optimal Inventory Policies when the Demand Distribution Is Not Known," Journal of Economic Theory, Elsevier, vol. 101(1), pages 281-300, November.
    3. Prak, Dennis & Teunter, Ruud & Syntetos, Aris, 2017. "On the calculation of safety stocks when demand is forecasted," European Journal of Operational Research, Elsevier, vol. 256(2), pages 454-461.
    4. Ghate, Archis, 2015. "Optimal minimum bids and inventory scrapping in sequential, single-unit, Vickrey auctions with demand learning," European Journal of Operational Research, Elsevier, vol. 245(2), pages 555-570.
    5. Halkos, George & Kevork, Ilias, 2012. "Evaluating alternative frequentist inferential approaches for optimal order quantities in the newsvendor model under exponential demand," MPRA Paper 39650, University Library of Munich, Germany.
    6. Bulinskaya, E. V., 2004. "Stochastic orders and inventory problems," International Journal of Production Economics, Elsevier, vol. 88(2), pages 125-135, March.
    7. Srinagesh Gavirneni & Roman Kapuscinski & Sridhar Tayur, 1999. "Value of Information in Capacitated Supply Chains," Management Science, INFORMS, vol. 45(1), pages 16-24, January.
    8. Sen, Alper & Zhang, Alex X., 2009. "Style goods pricing with demand learning," European Journal of Operational Research, Elsevier, vol. 196(3), pages 1058-1075, August.
    9. Katy S. Azoury & Julia Miyaoka, 2009. "Optimal Policies and Approximations for a Bayesian Linear Regression Inventory Model," Management Science, INFORMS, vol. 55(5), pages 813-826, May.
    10. Joseph M. Milner & Panos Kouvelis, 2002. "On the Complementary Value of Accurate Demand Information and Production and Supplier Flexibility," Manufacturing & Service Operations Management, INFORMS, vol. 4(2), pages 99-113, December.
    11. Zhang, Jian & Zhang, Juliang & Hua, Guowei, 2016. "Multi-period inventory games with information update," International Journal of Production Economics, Elsevier, vol. 174(C), pages 119-127.
    12. Srinagesh Gavirneni & Sridhar Tayur, 1999. "Managing a Customer Following a Target Reverting Policy," Manufacturing & Service Operations Management, INFORMS, vol. 1(2), pages 157-173.
    13. Bitran, Gabriel R. & Wadhwa, Hitendra K. S. (Hitendra Kumar Singh), 1996. "A methodology for demand learning with an application to the optimal pricing of seasonal products," Working papers 3898-96., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    14. Joseph M. Milner & Panos Kouvelis, 2005. "Order Quantity and Timing Flexibility in Supply Chains: The Role of Demand Characteristics," Management Science, INFORMS, vol. 51(6), pages 970-985, June.
    15. Glenn, David & Bisi, Arnab & Puterman, Martin L., 2004. "The Bayesian Newsvendors in Supply Chains with Unobserved Lost Sales," Working Papers 04-0110, University of Illinois at Urbana-Champaign, College of Business.
    16. Yossi Aviv, 2001. "The Effect of Collaborative Forecasting on Supply Chain Performance," Management Science, INFORMS, vol. 47(10), pages 1326-1343, October.
    17. Ananth V. Iyer & Vinayak Deshpande & Zhengping Wu, 2003. "A Postponement Model for Demand Management," Management Science, INFORMS, vol. 49(8), pages 983-1002, August.
    18. Alp Akcay & Bahar Biller & Sridhar Tayur, 2011. "Improved Inventory Targets in the Presence of Limited Historical Demand Data," Manufacturing & Service Operations Management, INFORMS, vol. 13(3), pages 297-309, July.

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