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Perishable inventory management system with a minimum volume constraint

Author

Listed:
  • Z Shen

    (University of Southern California, Los Angeles, USA)

  • M Dessouky

    (University of Southern California, Los Angeles, USA)

  • F Ordonez

    (University of Southern California, Los Angeles, USA)

Abstract

The federal government maintains large quantities of medical supplies in stock as part of its Strategic National Stockpile (SNS) to protect the American public in case of a public health emergency. Managing these large perishable inventories effectively can help reduce the cost of the SNS and improves national security. In this paper, we propose a modified Economic Manufacturing Quantity (EMQ) model for perishable inventory with a minimum volume constraint, which is applicable to managing the inventory of medicines for the Strategic National Stockpile. We demonstrate that minimizing the cost of maintaining such a system can be formulated as a non-convex non-smooth unconstrained optimization problem. The property of this model is analysed and an efficient exact algorithm is presented to solve this problem. In the numerical experiment part, we perform sensitivity analysis on several government-controlled system parameters to illustrate how the government can obtain lower costs or a larger stockpile at the same cost by allowing more freedom in the management of the stocks.

Suggested Citation

  • Z Shen & M Dessouky & F Ordonez, 2011. "Perishable inventory management system with a minimum volume constraint," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(12), pages 2063-2082, December.
    • Handle: RePEc:pal:jorsoc:v:62:y:2011:i:12:p:2063-2082
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    Cited by:

    1. Sachin Modgil & Sanjay Sharma, 2017. "Information Systems, Supply Chain Management and Operational Performance: Tri-linkage—An Exploratory Study on Pharmaceutical Industry of India," Global Business Review, International Management Institute, vol. 18(3), pages 652-677, June.
    2. Kawase, Riki & Iryo, Takamasa, 2023. "Optimal stochastic inventory-distribution strategy for damaged multi-echelon humanitarian logistics network," European Journal of Operational Research, Elsevier, vol. 309(2), pages 616-633.
    3. Wei Pan & Ying Guo & Wenji Zhang & Lei Jin & Shujie Liao, 2018. "Order policy for emergency medicine with return uncertainty in a closed-loop supply chain," PLOS ONE, Public Library of Science, vol. 13(10), pages 1-24, October.
    4. Zhou, Quan Spring & Olsen, Tava Lennon, 2017. "Inventory rotation of medical supplies for emergency response," European Journal of Operational Research, Elsevier, vol. 257(3), pages 810-821.
    5. Zhou, Quan Spring & Olsen, Tava Lennon, 2018. "Rotating the medical supplies for emergency response: A simulation based approach," International Journal of Production Economics, Elsevier, vol. 196(C), pages 1-11.
    6. Maddah, Bacel & Yassine, Ali A. & Salameh, Moueen K. & Chatila, Lama, 2014. "Reserve stock models: Deterioration and preventive replenishment," European Journal of Operational Research, Elsevier, vol. 232(1), pages 64-71.

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