Optimal Policy for Inventory Management with Periodic and Controlled Resets

Yoon Lee (), Yonatan Mintz (), Anil Aswani (), Zuo-Jun Max Shen () and Cong Yang ()
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Yoon Lee: Department of Industrial Engineering and Operations Research, University of California, Berkeley, Berkeley, California 94720
Yonatan Mintz: Department of Industrial and Systems Engineering, University of Wisconsin-Madison, Madison, Wisconsin 53706
Anil Aswani: Department of Industrial Engineering and Operations Research, University of California, Berkeley, Berkeley, California 94720
Zuo-Jun Max Shen: Department of Industrial Engineering and Operations Research, University of California, Berkeley, Berkeley, California 94720; and Faculty of Engineering and Faculty of Business and Economics, The University of Hong Kong, Hong Kong
Cong Yang: Sauder School of Business, University of British Columbia, Vancouver, British Columbia V6T 1Z2, Canada

Manufacturing & Service Operations Management, 2025, vol. 27, issue 5, 1484-1496

Abstract: Problem definition : Inventory management problems with periodic and controllable resets occur in the context of managing water storage in the developing world and dynamically optimizing endcap promotion duration in retail outlets. In this paper, we consider a set of sequential decision problems in which the decision maker must not only balance holding and shortage costs but discard all inventory before a fixed number of decision epochs with the option for an early inventory reset. Methodology/results : Finding optimal policies for these problems through dynamic programming presents unique challenges because of the nonconvex nature of the resulting value functions. Moreover, this structure cannot be readily analyzed even with extended convexity definitions, such as K -convexity. Managerial implications : Our key contribution is to present sufficient conditions that ensure the optimal policy has an easily interpretable structure, which generalizes the well-known ( s , S ) policy from the operations management literature. Furthermore, we demonstrate that, under these rather mild conditions, the optimal policy exhibits a four-threshold structure. We then conclude with computational experiments, thereby illustrating the policy structures that can be extracted in various inventory management scenarios.

Keywords: supply chain management; inventory theory and control; dynamic programming; healthcare management; humanitarian operations (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormsom:v:27:y:2025:i:5:p:1484-1496

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