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TECHNICAL NOTE---Optimal Control of an Assembly System with Multiple Stages and Multiple Demand Classes

Author

Listed:
  • Saif Benjaafar

    (Industrial and Systems Engineering, University of Minnesota, Minneapolis, Minnesota 55455)

  • Mohsen ElHafsi

    (The A. Gary Anderson Graduate School of Management, University of California, Riverside, California 92521)

  • Chung-Yee Lee

    (Department of Industrial Engineering and Logistics, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong)

  • Weihua Zhou

    (Department of Management Science and Engineering, Zhejiang University, Hangzhou, China)

Abstract

We consider an assembly system with multiple stages, multiple items, and multiple customer classes. The system consists of m production facilities, each producing a different item. Items are produced in variable batch sizes, one batch at a time, with exponentially distributed batch production times. Demand from each class takes place continuously over time according to a compound Poisson process. At each decision epoch, we must determine whether or not to produce an item and, should demand from a particular class arise, whether or not to satisfy it from existing inventory, if any is available. We formulate the problem as a Markov decision process and use it to characterize the structure of the optimal policy. In contrast to systems with exogenous and deterministic production lead times, we show that the optimal production policy for each item is a state-dependent base-stock policy with the base-stock level nonincreasing in the inventory level of items that are downstream and nondecreasing in the inventory level of all other items. For inventory allocation, we show that the optimal policy is a multilevel state-dependent rationing policy with the rationing level for each demand class nonincreasing in the inventory level of all nonend items. We also show how the optimal control problem can be reformulated in terms of echelon inventory and how the essential features of the optimal policy can be reinterpreted in terms of echelon inventory.

Suggested Citation

  • Saif Benjaafar & Mohsen ElHafsi & Chung-Yee Lee & Weihua Zhou, 2011. "TECHNICAL NOTE---Optimal Control of an Assembly System with Multiple Stages and Multiple Demand Classes," Operations Research, INFORMS, vol. 59(2), pages 522-529, April.
  • Handle: RePEc:inm:oropre:v:59:y:2011:i:2:p:522-529
    DOI: 10.1287/opre.1100.0889
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    References listed on IDEAS

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    1. Andrew J. Clark & Herbert Scarf, 2004. "Optimal Policies for a Multi-Echelon Inventory Problem," Management Science, INFORMS, vol. 50(12_supple), pages 1782-1790, December.
    2. Fangruo Chen & Yu-Sheng Zheng, 1994. "Lower Bounds for Multi-Echelon Stochastic Inventory Systems," Management Science, INFORMS, vol. 40(11), pages 1426-1443, November.
    3. Fangruo Chen, 2000. "Optimal Policies for Multi-Echelon Inventory Problems with Batch Ordering," Operations Research, INFORMS, vol. 48(3), pages 376-389, June.
    4. Saif Benjaafar & Mohsen ElHafsi, 2006. "Production and Inventory Control of a Single Product Assemble-to-Order System with Multiple Customer Classes," Management Science, INFORMS, vol. 52(12), pages 1896-1912, December.
    5. Kaj Rosling, 1989. "Optimal Inventory Policies for Assembly Systems Under Random Demands," Operations Research, INFORMS, vol. 37(4), pages 565-579, August.
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    Cited by:

    1. de Kok, Ton & Grob, Christopher & Laumanns, Marco & Minner, Stefan & Rambau, Jörg & Schade, Konrad, 2018. "A typology and literature review on stochastic multi-echelon inventory models," European Journal of Operational Research, Elsevier, vol. 269(3), pages 955-983.
    2. ElHafsi, Mohsen & Fang, Jianxin & Hamouda, Essia, 2020. "A novel decomposition-based method for solving general-product structure assemble-to-order systems," European Journal of Operational Research, Elsevier, vol. 286(1), pages 233-249.
    3. Gayon, Jean-Philippe & Vercraene, Samuel & Flapper, Simme Douwe P., 2017. "Optimal control of a production-inventory system with product returns and two disposal options," European Journal of Operational Research, Elsevier, vol. 262(2), pages 499-508.
    4. Emre Nadar & Mustafa Akan & Alan Scheller-Wolf, 2014. "Technical Note---Optimal Structural Results for Assemble-to-Order Generalized M -Systems," Operations Research, INFORMS, vol. 62(3), pages 571-579, June.
    5. Gregory A. DeCroix, 2013. "Inventory Management for an Assembly System Subject to Supply Disruptions," Management Science, INFORMS, vol. 59(9), pages 2079-2092, September.
    6. Martin Albrecht, 2021. "Component Allocation in Make-to-stock Assembly Systems," SN Operations Research Forum, Springer, vol. 2(2), pages 1-19, June.
    7. Albrecht, Martin, 2017. "Optimization of safety stocks in models with an order service level objective or constraint," European Journal of Operational Research, Elsevier, vol. 263(3), pages 900-909.
    8. Yi Yang & Jianan Wang & Youhua Chen & Zhiyuan Chen & Yanchu Liu, 2020. "Optimal procurement strategies for contractual assembly systems with fluctuating procurement price," Annals of Operations Research, Springer, vol. 291(1), pages 1027-1059, August.
    9. Zhan Pang & Frank Y. Chen & Youyi Feng, 2012. "Technical Note---A Note on the Structure of Joint Inventory-Pricing Control with Leadtimes," Operations Research, INFORMS, vol. 60(3), pages 581-587, June.

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