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The cost of using stationary inventory policies when demand is non-stationary

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  • Tunc, Huseyin
  • Kilic, Onur A.
  • Tarim, S. Armagan
  • Eksioglu, Burak
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    Abstract

    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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    Bibliographic Info

    Article provided by Elsevier in its journal Omega.

    Volume (Year): 39 (2011)
    Issue (Month): 4 (August)
    Pages: 410-415

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    Handle: RePEc:eee:jomega:v:39:y:2011:i:4:p:410-415

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    Related research

    Keywords: Inventory control Non-stationary demand Stationary policy (s; S) policy;

    References

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    1. Samuel Karlin, 1960. "Dynamic Inventory Policy with Varying Stochastic Demands," Management Science, INFORMS, vol. 6(3), pages 231-258, April.
    2. 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.
    3. 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.
    4. 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.
    5. Arthur F. Veinott, Jr. & Harvey M. Wagner, 1965. "Computing Optimal (s, S) Inventory Policies," Management Science, INFORMS, vol. 11(5), pages 525-552, March.
    6. 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.
    7. 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.
    8. 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.
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    Cited by:
    1. Tempelmeier, Horst, 2011. "A column generation heuristic for dynamic capacitated lot sizing with random demand under a fill rate constraint," Omega, Elsevier, vol. 39(6), pages 627-633, December.
    2. Özen, Ulaş & Doğru, Mustafa K. & Armagan Tarim, S., 2012. "Static-dynamic uncertainty strategy for a single-item stochastic inventory control problem," Omega, Elsevier, vol. 40(3), pages 348-357.

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