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Perishable inventory management system with a minimum volume constraint

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  • Z Shen

    (University of Southern California)

  • M Dessouky

    (University of Southern California)

  • F Ordonez

    (University of Southern California)

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:d:10.1057_jors.2010.181
    DOI: 10.1057/jors.2010.181
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    References listed on IDEAS

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    1. William P. Pierskalla & Chris D. Roach, 1972. "Optimal Issuing Policies for Perishable Inventory," Management Science, INFORMS, vol. 18(11), pages 603-614, July.
    2. Guillermo Gallego & Garrett van Ryzin, 1994. "Optimal Dynamic Pricing of Inventories with Stochastic Demand over Finite Horizons," Management Science, INFORMS, vol. 40(8), pages 999-1020, August.
    3. Katagiri, Hideki & Ishii, Hiroaki, 2002. "Fuzzy inventory problems for perishable commodities," European Journal of Operational Research, Elsevier, vol. 138(3), pages 545-553, May.
    4. Donald B. Rosenfield, 1992. "Optimality of Myopic Policies in Disposing Excess Inventory," Operations Research, INFORMS, vol. 40(4), pages 800-803, August.
    5. Ravichandran, N., 1995. "Stochastic analysis of a continuous review perishable inventory system with positive lead time and Poisson demand," European Journal of Operational Research, Elsevier, vol. 84(2), pages 444-457, July.
    6. Chon-Huat Goh & Betsy S. Greenberg & Hirofumi Matsuo, 1993. "Two-Stage Perishable Inventory Models," Management Science, INFORMS, vol. 39(5), pages 633-649, May.
    7. Vernon Ning Hsu & Timothy J. Lowe, 2001. "Dynamic Economic Lot Size Models with Period-Pair-Dependent Backorder and Inventory Costs," Operations Research, INFORMS, vol. 49(2), pages 316-321, April.
    8. Chun, Young H., 2003. "Optimal pricing and ordering policies for perishable commodities," European Journal of Operational Research, Elsevier, vol. 144(1), pages 68-82, January.
    9. Stephen C. Graves, 1982. "The Application of Queueing Theory to Continuous Perishable Inventory Systems," Management Science, INFORMS, vol. 28(4), pages 400-406, April.
    10. Liming Liu & Zhaotong Lian, 1999. "(s, S) Continuous Review Models for Products with Fixed Lifetimes," Operations Research, INFORMS, vol. 47(1), pages 150-158, February.
    11. Matthew J. Sobel & Rachel Q. Zhang, 2001. "Inventory Policies for Systems with Stochastic and Deterministic Demand," Operations Research, INFORMS, vol. 49(1), pages 157-162, February.
    12. Steven Nahmias, 1982. "Perishable Inventory Theory: A Review," Operations Research, INFORMS, vol. 30(4), pages 680-708, August.
    13. Dan Chazan & Shmuel Gal, 1977. "A Markovian Model for a Perishable Product Inventory," Management Science, INFORMS, vol. 23(5), pages 512-521, January.
    14. Purushottaman Nandakumar & Thomas E. Morton, 1993. "Near Myopic Heuristics for the Fixed-Life Perishability Problem," Management Science, INFORMS, vol. 39(12), pages 1490-1498, December.
    15. Donald B. Rosenfield, 1989. "Disposal of Excess Inventory," Operations Research, INFORMS, vol. 37(3), pages 404-409, June.
    16. Giri, B.C. & Chaudhuri, K.S., 1998. "Deterministic models of perishable inventory with stock-dependent demand rate and nonlinear holding cost," European Journal of Operational Research, Elsevier, vol. 105(3), pages 467-474, March.
    17. Apostolos N. Burnetas & Craig E. Smith, 2000. "Adaptive Ordering and Pricing for Perishable Products," Operations Research, INFORMS, vol. 48(3), pages 436-443, June.
    18. Harvey M. Wagner & Thomson M. Whitin, 1958. "Dynamic Version of the Economic Lot Size Model," Management Science, INFORMS, vol. 5(1), pages 89-96, October.
    19. Vernon Ning Hsu, 2000. "Dynamic Economic Lot Size Model with Perishable Inventory," Management Science, INFORMS, vol. 46(8), pages 1159-1169, August.
    20. Howard J. Weiss, 1980. "Optimal Ordering Policies for Continuous Review Perishable Inventory Models," Operations Research, INFORMS, vol. 28(2), pages 365-374, April.
    21. P. L. Abad, 1996. "Optimal Pricing and Lot-Sizing Under Conditions of Perishability and Partial Backordering," Management Science, INFORMS, vol. 42(8), pages 1093-1104, August.
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    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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