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The Fixed-Charge Perishable Inventory Problem

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  • Steven Nahmias

    (University of Pittsburgh, Pittsburgh, Pennsylvania)

Abstract

This paper deals with the problem of determing both optimal and approximate ordering policies for a fixed-life perishable commodity when there is a fixed charge or set-up cost for placing an order. The structure of the optimal policy can be inferred from the analysis of a one-period model under the assumption that the outdating is paid for when the order arrives rather than when the outdating actually occurs. An approximate model is constructed for which ( s , S ) policies are optimal by approximating the one expected single-period cost and the transfer function. Two different bounds on the expected out-dating per period are used to obtain two different ( s , S ) approximations. Computations are performed for a discrete version of the problem with three different demand distributions and 24 configurations of the cost structure to compare the effectiveness of both approximations with the optimal policy.

Suggested Citation

  • Steven Nahmias, 1978. "The Fixed-Charge Perishable Inventory Problem," Operations Research, INFORMS, vol. 26(3), pages 464-481, June.
    • Handle: RePEc:inm:oropre:v:26:y:1978:i:3:p:464-481
    DOI: 10.1287/opre.26.3.464
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    Cited by:

    1. Lian, Zhaotong & Liu, Xiaoming & Zhao, Ning, 2009. "A perishable inventory model with Markovian renewal demands," International Journal of Production Economics, Elsevier, vol. 121(1), pages 176-182, September.
    2. Huanan Zhang & Cong Shi & Xiuli Chao, 2016. "Technical Note—Approximation Algorithms for Perishable Inventory Systems with Setup Costs," Operations Research, INFORMS, vol. 64(2), pages 432-440, April.
    3. Kouki, Chaaben & Jemaï, Zied & Minner, Stefan, 2015. "A lost sales (r, Q) inventory control model for perishables with fixed lifetime and lead time," International Journal of Production Economics, Elsevier, vol. 168(C), pages 143-157.
    4. 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.
    5. Elena Katok & Andrew Lathrop & William Tarantino & Susan H. Xu, 2001. "Jeppesen Uses a Dynamic-Programming-Based DSS to Manage Inventory," Interfaces, INFORMS, vol. 31(6), pages 54-65, December.
    6. Ding, Jingying & Peng, Zhenkang, 2024. "Heuristics for perishable inventory systems under mixture issuance policies," Omega, Elsevier, vol. 126(C).
    7. Widodo, K.H. & Nagasawa, H. & Morizawa, K. & Ota, M., 2006. "A periodical flowering-harvesting model for delivering agricultural fresh products," European Journal of Operational Research, Elsevier, vol. 170(1), pages 24-43, April.
    8. William L. Cooper, 2001. "Pathwise Properties and Performance Bounds for a Perishable Inventory System," Operations Research, INFORMS, vol. 49(3), pages 455-466, June.
    9. Ensafian, Hamidreza & Yaghoubi, Saeed, 2017. "Robust optimization model for integrated procurement, production and distribution in platelet supply chain," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 103(C), pages 32-55.
    10. Kouki, Chaaben & Jouini, Oualid, 2015. "On the effect of lifetime variability on the performance of inventory systems," International Journal of Production Economics, Elsevier, vol. 167(C), pages 23-34.
    11. Kouki, Chaaben & Sahin, Evren & Jemaï, Zied & Dallery, Yves, 2013. "Assessing the impact of perishability and the use of time temperature technologies on inventory management," International Journal of Production Economics, Elsevier, vol. 143(1), pages 72-85.
    12. Tekin, Eylem & Gurler, Ulku & Berk, Emre, 2001. "Age-based vs. stock level control policies for a perishable inventory system," European Journal of Operational Research, Elsevier, vol. 134(2), pages 309-329, October.
    13. Maloni, Michael J. & Benton, W.C., 1997. "Supply chain partnerships: Opportunities for operations research," European Journal of Operational Research, Elsevier, vol. 101(3), pages 419-429, September.
    14. Wang, Ke-Ming & Ma, Zu-Jun, 2015. "Age-based policy for blood transshipment during blood shortage," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 80(C), pages 166-183.
    15. 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.

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