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Rolling Horizon Procedures for the Facilities in Series Inventory Model with Nested Schedules

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  • Suresh Chand

    (Purdue University)

Abstract

This paper develops rolling horizon procedures for solving a multistage inventory problem with facilities-in-series. In such an inventory system, we assume that the raw material is processed successively through several facilities before reaching the customer. The input to a facility comes from one preceding facility (or the raw material) and the output from the facility goes to one succeeding facility (or the customer). The rolling horizon procedures form rolling production schedules by solving a finite horizon multiperiod problem and implementing only the first period's decisions. One period later, the multiperiod problem is updated as better forecasts become available and the process is repeated. The paper considers a simple case when holding costs are linear, production costs on a facility consist of a setup cost and a constant marginal cost of production, and production and holding costs are stationary in time. Demand is allowed to be nonstationary in time. Several rolling horizon procedures are developed for this case and a computational comparison is given.

Suggested Citation

  • Suresh Chand, 1983. "Rolling Horizon Procedures for the Facilities in Series Inventory Model with Nested Schedules," Management Science, INFORMS, vol. 29(2), pages 237-249, February.
    • Handle: RePEc:inm:ormnsc:v:29:y:1983:i:2:p:237-249
    DOI: 10.1287/mnsc.29.2.237
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    Citations

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    Cited by:

    1. Dellaert, Nico & Jeunet, Jully, 2003. "Controlling multi-level production in a rolling-schedule environment," International Journal of Production Economics, Elsevier, vol. 85(1), pages 113-121, July.
    2. repec:dau:papers:123456789/2078 is not listed on IDEAS
    3. Zhang, Jianghua & Long, Daniel Zhuoyu & Li, Yuchen, 2023. "A reliable emergency logistics network for COVID-19 considering the uncertain time-varying demands," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 172(C).
    4. Voros, Jozsef, 1995. "Setup cost stability region for the multi-level dynamic lot sizing problem," European Journal of Operational Research, Elsevier, vol. 87(1), pages 132-141, November.
    5. Jing, Fuying & Chao, Xiangrui, 2022. "Forecast horizons for a two-echelon dynamic lot-sizing problem," Omega, Elsevier, vol. 110(C).
    6. Kedar S. Naphade & S. David Wu & Robert H. Storer & Bhavin J. Doshi, 2001. "Melt Scheduling to Trade Off Material Waste and Shipping Performance," Operations Research, INFORMS, vol. 49(5), pages 629-645, October.
    7. Richter, Knut & Gobsch, Barbara, 2003. "The market-oriented dynamic product recovery model in the just-in-time framework," International Journal of Production Economics, Elsevier, vol. 81(1), pages 369-374, January.
    8. Z Hua & J Yang & F Huang & X Xu, 2009. "A static-dynamic strategy for spare part inventory systems with nonstationary stochastic demand," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(9), pages 1254-1263, September.
    9. Dellaert, N. & Jeunet, J., 2005. "An alternative to safety stock policies for multi-level rolling schedule MRP problems," European Journal of Operational Research, Elsevier, vol. 163(3), pages 751-768, June.
    10. Suresh Chand & Vernon Ning Hsu & Suresh Sethi, 2002. "Forecast, Solution, and Rolling Horizons in Operations Management Problems: A Classified Bibliography," Manufacturing & Service Operations Management, INFORMS, vol. 4(1), pages 25-43, September.

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