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A Single-Product Inventory Model for Multiple Demand Classes

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  • Arslan, Hasan
  • Graves, Stephen C.
  • Roemer, Thomas

Abstract

We consider a single-product inventory system that serves multiple demand classes, which differ in their shortage costs or service level requirements. We assume a critical-level control policy, and show the equivalence between this inventory system and a serial inventory system. Based on this equivalence, we develop a model for cost evaluation and optimization, under the assumptions of Poisson demand, deterministic replenishment lead-time, and a continuous-review (Q, R) policy with rationing. We propose a computationally-efficient heuristic and develop a bound on its performance. We provide a numerical experiment to show the effectiveness of the heuristic and the value from a rationing policy. Finally, we describe how to extend the model to permit service times, and to embed within a multi-echelon setting.

Suggested Citation

  • Arslan, Hasan & Graves, Stephen C. & Roemer, Thomas, 2005. "A Single-Product Inventory Model for Multiple Demand Classes," Working papers 4542-05, Massachusetts Institute of Technology (MIT), Sloan School of Management.
    • Handle: RePEc:mit:sloanp:17071
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    File URL: http://hdl.handle.net/1721.1/17071
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    References listed on IDEAS

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    1. Stephen C. Graves, 1985. "A Multi-Echelon Inventory Model for a Repairable Item with One-for-One Replenishment," Management Science, INFORMS, vol. 31(10), pages 1247-1256, October.
    2. Donald M. Topkis, 1968. "Optimal Ordering and Rationing Policies in a Nonstationary Dynamic Inventory Model with n Demand Classes," Management Science, INFORMS, vol. 15(3), pages 160-176, November.
    3. P Melchiors & R Dekker & M J Kleijn, 2000. "Inventory rationing in an (s, Q) inventory model with lost sales and two demand classes," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 51(1), pages 111-122, January.
    4. Steven Nahmias & W. Steven Demmy, 1981. "Operating Characteristics of an Inventory System with Rationing," Management Science, INFORMS, vol. 27(11), pages 1236-1245, November.
    5. Arthur F. Veinott, 1965. "Optimal Policy in a Dynamic, Single Product, Nonstationary Inventory Model with Several Demand Classes," Operations Research, INFORMS, vol. 13(5), pages 761-778, October.
    6. Katia C. Frank & Rachel Q. Zhang & Izak Duenyas, 2003. "Optimal Policies for Inventory Systems with Priority Demand Classes," Operations Research, INFORMS, vol. 51(6), pages 993-1002, December.
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    Cited by:

    1. Teunter, Ruud H. & Klein Haneveld, Willem K., 2008. "Dynamic inventory rationing strategies for inventory systems with two demand classes, Poisson demand and backordering," European Journal of Operational Research, Elsevier, vol. 190(1), pages 156-178, October.
    2. Mohammad Najjartabar Bisheh & G. Reza Nasiri & Esmaeil Esmaeili & Hamid Davoudpour & Shing I. Chang, 2022. "A new supply chain distribution network design for two classes of customers using transfer recurrent neural network," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(5), pages 2604-2618, October.
    3. Quante, R. & Meyr, H. & Fleischmann, M., 2007. "Revenue Management and Demand Fulfillment: Matching Applications, Models, and Software," ERIM Report Series Research in Management ERS-2007-050-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    4. FadIloglu, Mehmet Murat & Bulut, Önder, 2010. "A dynamic rationing policy for continuous-review inventory systems," European Journal of Operational Research, Elsevier, vol. 202(3), pages 675-685, May.

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