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Robustness of Order-Up-to Policies in Lost-Sales Inventory Systems

Author

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  • Marco Bijvank

    (Haskayne School of Business, University of Calgary, Calgary, Alberta T2N 1N4, Canada)

  • Woonghee Tim Huh

    (Sauder School of Business, University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada)

  • Ganesh Janakiraman

    (Naveen Jindal School of Management, University of Texas at Dallas, Richardson, Texas 75080,)

  • Wanmo Kang

    (Department of Mathematical Sciences, Korea Advanced Institute of Science and Technology, Daejeon, 305-701, South Korea)

Abstract

We study an inventory system under periodic review when excess demand is lost. It is known (Huh et al. 2009) that the best base-stock policy is asymptotically optimal as the lost-sales penalty cost parameter grows. We now show that this result is robust in the following sense: Consider the base-stock level which is optimal in a backordering system (with a per-unit-per-period backordering cost) in which the backorder cost parameter is a function of the lost-sales parameter in the original system. Then there is a large family of functions (mapping the lost-sales cost parameter to the backorder cost parameter) such that the resulting base-stock policy is asymptotically optimal. We also demonstrate the robustness phenomenon through a second result. We consider the base-stock level which is optimal in a backordering system in which a unit of backorder is charged a penalty cost only once (such a system has been studied by Rosling). We show that this base-stock policy is also asymptotically optimal. Furthermore, we show that a modification suggested by Archibald of this base-stock level also results in an asymptotically optimal policy. Finally, we numerically test the performance of this heuristic policy for a wide spectrum of values for the lost-sales penalty cost parameter and illustrate the superior performance of Archibald's method.

Suggested Citation

  • Marco Bijvank & Woonghee Tim Huh & Ganesh Janakiraman & Wanmo Kang, 2014. "Robustness of Order-Up-to Policies in Lost-Sales Inventory Systems," Operations Research, INFORMS, vol. 62(5), pages 1040-1047, October.
    • Handle: RePEc:inm:oropre:v:62:y:2014:i:5:p:1040-1047
    DOI: 10.1287/opre.2014.1298
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    References listed on IDEAS

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    Cited by:

    1. Kouki, Chaaben & Babai, M. Zied & Jemai, Zied & Minner, Stefan, 2019. "Solution procedures for lost sales base-stock inventory systems with compound Poisson demand," International Journal of Production Economics, Elsevier, vol. 209(C), pages 172-182.
    2. Sasanuma, Katsunobu & Delasay, Mohammad & Pitocco, Christine & Scheller-Wolf, Alan & Sexton, Thomas, 2022. "A marginal analysis framework to incorporate the externality effect of ordering perishables," Operations Research Perspectives, Elsevier, vol. 9(C).
    3. Kouki, Chaaben & Arts, Joachim & Babai, M. Zied, 2024. "Performance evaluation of a two-echelon inventory system with network lost sales," European Journal of Operational Research, Elsevier, vol. 314(2), pages 647-664.
    4. Manuel Cardós & Ester Guijarro & Eugenia Babiloni, 2017. "On the estimation of on-hand stocks for base-stock policies and lost sales systems and its impact on service measures," International Journal of Production Research, Taylor & Francis Journals, vol. 55(16), pages 4680-4694, August.
    5. Yanyi Xu & Sang-Phil Kim & Arnab Bisi & Maqbool Dada & Suresh Chand, 2018. "Base-Stock Models for Lost Sales: A Markovian Approach," Purdue University Economics Working Papers 1305, Purdue University, Department of Economics.
    6. Jinzhi Bu & Xiting Gong & Xiuli Chao, 2023. "Asymptotic Optimality of Base-Stock Policies for Perishable Inventory Systems," Management Science, INFORMS, vol. 69(2), pages 846-864, February.
    7. Huanan Zhang & Xiuli Chao & Cong Shi, 2020. "Closing the Gap: A Learning Algorithm for Lost-Sales Inventory Systems with Lead Times," Management Science, INFORMS, vol. 66(5), pages 1962-1980, May.
    8. Sasanuma, Katsunobu & Hibiki, Akira & Sexton, Thomas, 2022. "An opaque selling scheme to reduce shortage and wastage in perishable inventory systems," Operations Research Perspectives, Elsevier, vol. 9(C).

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