The cost of using stationary inventory policies when demand is non-stationary
Non-stationary stochastic demands are very common in industrial settings with seasonal patterns, trends, business cycles, and limited-life items. In such cases, the optimal inventory control policies are also non-stationary. However, due to high computational complexity, non-stationary inventory policies are not usually preferred in real-life applications. In this paper, we investigate the cost of using a stationary policy as an approximation to the optimal non-stationary one. Our numerical study points to two important results: (i) Using stationary policies can be very expensive depending on the magnitude of demand variability. (ii) Stationary policies may be efficient approximations to optimal non-stationary policies when demand information contains high uncertainty, setup costs are high and penalty costs are low.
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Volume (Year): 39 (2011)
Issue (Month): 4 (August)
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- Tarim, S. Armagan & Kingsman, Brian G., 2006. "Modelling and computing (Rn, Sn) policies for inventory systems with non-stationary stochastic demand," European Journal of Operational Research, Elsevier, vol. 174(1), pages 581-599, October.
- Yue, Jinfeng & Xia, Yu & Tran, Thuhang, 2010. "Selecting sourcing partners for a make-to-order supply chain," Omega, Elsevier, vol. 38(3-4), pages 136-144, June.
- Wang, Kung-Jeng & Wee, Hui-Ming & Gao, Shin-Feng & Chung, Shen-Lian, 2005. "Production and inventory control with chaotic demands," Omega, Elsevier, vol. 33(2), pages 97-106, April.
- Arthur F. Veinott, Jr. & Harvey M. Wagner, 1965. "Computing Optimal (s, S) Inventory Policies," Management Science, INFORMS, vol. 11(5), pages 525-552, March.
- Donald L. Iglehart, 1963. "Optimality of (s, S) Policies in the Infinite Horizon Dynamic Inventory Problem," Management Science, INFORMS, vol. 9(2), pages 259-267, January.
- Samuel Karlin, 1960. "Dynamic Inventory Policy with Varying Stochastic Demands," Management Science, INFORMS, vol. 6(3), pages 231-258, April.
- Mohebbi, E. & Choobineh, F., 2005. "The impact of component commonality in an assemble-to-order environment under supply and demand uncertainty," Omega, Elsevier, vol. 33(6), pages 472-482, December.
- Stephen C. Graves & Sean P. Willems, 2008. "Strategic Inventory Placement in Supply Chains: Nonstationary Demand," Manufacturing & Service Operations Management, INFORMS, vol. 10(2), pages 278-287, March.
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