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Approximation Algorithms for Capacitated Perishable Inventory Systems with Positive Lead Times

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  • Xiuli Chao

    (Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, Michigan 48109)

  • Xiting Gong

    (Department of Systems Engineering and Engineering Management, Faculty of Engineering, Chinese University of Hong Kong, Shatin, N.T., Hong Kong; Department of Decision Sciences and Managerial Economics, CUHK Business School, Chinese University of Hong Kong, Shatin, N.T., Hong Kong)

  • Cong Shi

    (Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, Michigan 48109)

  • Chaolin Yang

    (Research Institute for Interdisciplinary Sciences, School of Information Management and Engineering, Shanghai University of Finance and Economics, 200433 Shanghai, China)

  • Huanan Zhang

    (Harold and Inge Marcus Department of Industrial and Manufacturing Engineering, Pennsylvania State University, University Park, Pennsylvania 16802)

  • Sean X. Zhou

    (Department of Decision Sciences and Managerial Economics, CUHK Business School, Chinese University of Hong Kong, Shatin, N.T., Hong Kong)

Abstract

Managing perishable inventory systems with positive lead times and finite ordering capacities is important but notoriously difficult in both theory and computation. The optimal control policy is extremely complicated, and no effective heuristic policy has been proposed in the literature. In this paper, we develop an easy-to-compute approximation algorithm for this class of problems and prove that it admits a theoretical worst-case performance guarantee under independent and many commonly used positively correlated demand processes. Our worst-case analysis departs significantly from those in the previous studies, requiring several novel ideas. In particular, we introduce a transient unit-matching rule to dynamically match the supply and demand units, and the notion of associated demand processes that provides the right future demand information to establish the desired results. Our numerical study demonstrates the effectiveness of the proposed algorithm.

Suggested Citation

  • Xiuli Chao & Xiting Gong & Cong Shi & Chaolin Yang & Huanan Zhang & Sean X. Zhou, 2018. "Approximation Algorithms for Capacitated Perishable Inventory Systems with Positive Lead Times," Management Science, INFORMS, vol. 64(11), pages 5038-5061, November.
    • Handle: RePEc:inm:ormnsc:v:64:y:2018:i:11:p:5038-5061
    DOI: 10.1287/mnsc.2017.2886
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    References listed on IDEAS

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    5. Harun Avci & Kagan Gokbayrak & Emre Nadar, 2020. "Structural Results for Average‐Cost Inventory Models with Markov‐Modulated Demand and Partial Information," Production and Operations Management, Production and Operations Management Society, vol. 29(1), pages 156-173, January.
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