JSSM  Vol.7 No.1 , February 2014
Perishable Inventory Management in Healthcare
Abstract: This study addresses a problem encountered in a nation-wide, large-scale healthcare supply chain that comprises several hundred medical organizations (hospitals, clinics, pharmacies, etc.) and provides highly advanced medical care to several million people. The medical products in the system are perishable, meaning that they become unusable beyond a certain expiry date. It is necessary to track the ages of units in stock and to plan and control the inventory accordingly. The models developed herein represent a multi-echelon, multi-supplier inventory system and unite together aspects of perishability and outsourcing under deterministic demand for medical products, which include both perishable and deteriorating goods. The objective of the study is to determine the optimal number of products to be purchased from regular and outsource suppliers so as to meet the required demand at the minimum operating cost. The solution is a network-flow model that can be used to determine the trade-off between the quantities of items to be ordered from the two types of suppliers in each time period. In addition, the study analyzes different distribution policies to account for the perishable nature of the products. Further insights are obtained by applying the model to a case study of a real-life healthcare supply chain from which interesting results are drawn.
Cite this paper: Perlman, Y. and Levner, I. (2014) Perishable Inventory Management in Healthcare. Journal of Service Science and Management, 7, 11-17. doi: 10.4236/jssm.2014.71002.

[1]   Y. Ge and J. Zhang, “Dynamic Pricing of Perishable Products under Consumer Factor,” Journal of Service Science and Management, Vol. 4, No. 4, 2011, pp. 440-444.

[2]   S. Nahmias, “Perishable Inventory Theory: A Review,” Operations Research, Vol. 30, No. 4, 1982, pp. 680-708.

[3]   Z. Shen, M. Dessouky and F. Ordonez,“Perishable Inventory Management System with a Minimum Volume Constraint,” Journal of the Operational Research Society, Vol. 62, No. 12, 2011, pp. 2063-2082.

[4]   A. Atamturk and D. S.Hochbaum, “Capacity Acquisition, Subcontracting and Lot Sizing,” Management Science, Vol. 47, No. 8, 2001, pp. 1081-1100.

[5]   X. Liu, C. Wang, X. Luo and D. Wang, “A Model and Algorithm for Outsourcing Planning,” Proceedings of the 2005 IEEE International Conference on E-Business Engineering, ICEBE’05, Beijing, 2005, pp. 1-4.

[6]   X. Liu and J. Zhang, “A Capacitated Production Planning with Outsourcing: A General Model and Its Algorithm,” Lecture Notes in Computer Science, Vol. 4113, No. 2006, pp. 997-1002.

[7]   C. Chu, F. Chu, J. Zhong and S. Yang, “A Polynomial Algorithm for a Lot-Sizing Problem with Backlogging, Outsourcing and Limited Inventory,” Computers & Industrial Engineering, Vol. 52, No. 1, 2013, pp. 200-210.

[8]   S. K. Goyal and B. C. Giri, “Recent Trends in Modeling of Deteriorating Inventory,” European Journal of Operational Research, Vol. 134, No. 1, 2001, pp. 1-16.

[9]   M. Bakker, J. Riezebos and R. H. Teunter, “Review of Inventory Systems with Deterioration since 2001,” European Journal of Operational Research, Vol. 221, No. 2, 2012, pp. 275-284.

[10]   H. M. Wagner and T. M. Whitin, “A Dynamic Version of the Economic Lot Size Model,” Management Science, Vol. 5, No. 1, 1958, pp. 89-96.

[11]   M. Florian and M. Klein, “Deterministic Production Planning with Concave Costs and Capacity Constraints,” Management Science, Vol. 18, No. 1, 1971, pp. 12-20.

[12]   W. I. Zangwill, “Minimum Concave Cost Flows in Certain Networks,” Management Science, Vol. 14, No. 7, 1968, pp. 429-450.

[13]   W. I. Zangwill, “A Backlogging Model and a Multi-Echelon Model of a Dynamic Economic Lot Size Production System—A Network Approach,” Management Science, Vol. 15, No. 9, 1969, pp. 506-527.

[14]   Y. Perlman and I. Levner, “Modeling Multi-Echelon Multi-Supplier Repairable Inventory Systems with Backorders,” Journal of Service Science & Management, Vol. 3, No. 4, 2010, pp. 440-448.

[15]   E. Levner, Y. Perlman, T. C. E. Cheng and I. Levner, “A Network Approach to Modeling the Multi-Echelon Spare Part Inventory System with Backorders and Interval-Valued Demand,” International Journal of Production Economics, Vol. 132, No. 1, 2011, pp. 43-51.

[16]   P. Nandakumar and T. E. Morton, “Near Myopic Heuristic for the Fixed Life Perishability Problem,” Management Science, Vol. 18, 1990, pp. 1490-1498.

[17]   L. R. Weatherford and S. E. Bodily, “A Taxonomy and Research Overview of Perishable-Asset Revenue Management: Yield Management Overbooking and Pricing,” Operations Research, Vol. 40, No. 5, 1992, pp. 831-844.

[18]   A. Aggarwal and J. K. Park, “Improved Algorithms for Economic Lot Size Problems,” Operations Research, Vol. 41, No. 3, 1993, pp. 49-571.

[19]   V. N. Hsu, “Dynamic Economic Lot Size Model with Perishable Inventory,” Management Science, Vol. 46, No. 8, 2000, pp. 1159-1169.

[20]   L. Y. Chu, V. H. Hsu and Z. J. M. Shen, “An Economic Lot Sizing Problem with Perishable Inventory and Economic of Scale Costs: Approximation Solutions and Worst Case Analysis,” Naval Research Logistics, Vol. 52, No. 6, 2005, pp. 536-548.

[21]   N. Brahimi, S. Dauzere-Peres, N. Najid and A. Nordl, “Single Item Lot Sizing Problems,” European Journal of Operational Research, Vol. 168, No. 1, 2006, pp. 1-16.

[22]   Q. G. Bai, Y. Z. Zhang and G. L. Dong, “A Note on Economic Lot Sizing Problem with Perishable Inventory And Economies of Scale Costs: Approximation Solutions and Worst-Case Analysis,” International Journal of Automation and Computing, Vol. 7, No. 1, 2010, pp. 132-136.

[23]   J. Yang, X. Qi and Y. Xia, “A Production-Inventory System with Markovian Capacity and Outsourcing Option,” Operations Research, Vol. 53, No. 2, 2005, pp. 328-349.

[24]   S. Chand, V. N. Hsu, S. Sethi and V. Deshpande, “A Dynamic Lot Size Problem with Multiple Customers: Customer-Specific Shipping and Backlogging Costs,” IIE Transactions, Vo. 39, No. 11, 2007, pp. 1059-1069.