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Optimal ordering policies for a product that perishes in two periods subject to stochastic demand

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  • Steven Nahmias
  • William P. Pierskalla

Abstract

This paper considers the problem of computing optimal ordering policies for a product that has a life of exactly two periods when demand is random. Initially costs are charged against runouts (stockouts) and outdating (perishing). By charging outdating costs according to the expected amount of outdating one period into the future, a feasible one period model is constructed. The central theorem deals with the n‐stage dynamic problem and demonstrates the appropriate cost functions are convex in the decision variable and also provides bounds on certain derivatives. The model is then generalized to include ordering and holding costs. The paper is concluded with a discussion of the infinite horizon problem.

Suggested Citation

  • Steven Nahmias & William P. Pierskalla, 1973. "Optimal ordering policies for a product that perishes in two periods subject to stochastic demand," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 20(2), pages 207-229, June.
    • Handle: RePEc:wly:navlog:v:20:y:1973:i:2:p:207-229
    DOI: 10.1002/nav.3800200202
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    Cited by:

    1. Tomoaki Yamazaki & Keisuke Shida & Takashi Kanazawa, 2016. "An approach to establishing a method for calculating inventory," International Journal of Production Research, Taylor & Francis Journals, vol. 54(8), pages 2320-2331, April.
    2. Hossein Abouee‐Mehrizi & Mahdi Mirjalili & Vahid Sarhangian, 2022. "Data‐driven platelet inventory management under uncertainty in the remaining shelf life of units," Production and Operations Management, Production and Operations Management Society, vol. 31(10), pages 3914-3932, October.
    3. Lowalekar, Harshal & Ravi, R. Raghavendra, 2017. "Revolutionizing blood bank inventory management using the TOC thinking process: An Indian case study," International Journal of Production Economics, Elsevier, vol. 186(C), pages 89-122.
    4. Jake Clarkson & Michael A. Voelkel & Anna‐Lena Sachs & Ulrich W. Thonemann, 2023. "The periodic review model with independent age‐dependent lifetimes," Production and Operations Management, Production and Operations Management Society, vol. 32(3), pages 813-828, March.
    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. Kebing Chen & Jing‐Sheng Song & Jennifer Shang & Tiaojun Xiao, 2022. "Managing hospital platelet inventory with mid‐cycle expedited replenishments and returns," Production and Operations Management, Production and Operations Management Society, vol. 31(5), pages 2015-2037, May.
    7. Ding, Jingying & Peng, Zhenkang, 2024. "Heuristics for perishable inventory systems under mixture issuance policies," Omega, Elsevier, vol. 126(C).
    8. Zahra Azadi & Harsha Gangammanavar & Sandra Eksioglu, 2020. "Developing childhood vaccine administration and inventory replenishment policies that minimize open vial wastage," Annals of Operations Research, Springer, vol. 292(1), pages 215-247, September.
    9. Hailun Zhang & Jiheng Zhang & Rachel Q. Zhang, 2020. "Simple Policies with Provable Bounds for Managing Perishable Inventory," Production and Operations Management, Production and Operations Management Society, vol. 29(11), pages 2637-2650, November.
    10. Xiong‐zhi Wang & Guo‐qing Wang, 2019. "Integrating dynamic pricing and inventory control for fresh‐agri product under consumer choice," Australian Economic Papers, Wiley Blackwell, vol. 58(1), pages 96-111, March.
    11. 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).
    12. 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.
    13. M. Rezaei Kallaj & M. Hasannia Kolaee & S. M. J. Mirzapour Al-e-hashem, 2023. "Integrating bloodmobiles and drones in a post-disaster blood collection problem considering blood groups," Annals of Operations Research, Springer, vol. 321(1), pages 783-811, February.
    14. Ketzenberg, Michael & Oliva, Rogelio & Wang, Yimin & Webster, Scott, 2023. "Retailer inventory data sharing in a fresh product supply chain," European Journal of Operational Research, Elsevier, vol. 307(2), pages 680-693.
    15. Chua, Geoffrey A. & Senga, Juan Ramon L., 2022. "Blood supply interventions during disasters: Efficiency measures and strategies to mitigate volatility," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).

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