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Effective Zero-Inventory-Ordering Policies for the Single-Warehouse Multiretailer Problem with Piecewise Linear Cost Structures

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Author Info

  • Lap Mui Ann Chan

    ()
    (School of Management, University of Toronto, Toronto, Ontario, Canada)

  • Ana Muriel

    ()
    (Department of Mechanical and Industrial Engineering, University of Massachusetts, Amherst, Massachusetts)

  • Zuo-Jun Max Shen

    ()
    (Department of Industrial and Systems Engineering, University of Florida, Gainesville, Florida)

  • David Simchi-Levi

    ()
    (The Engineering Systems Division and the Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts)

  • Chung-Piaw Teo

    ()
    (Department of Decision Sciences, National University of Singapore, Singapore)

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    Abstract

    We analyze the problem faced by companies that rely on TL (Truckload) and LTL (Less than Truckload) carriers for the distribution of products across their supply chain. Our goal is to design simple inventory policies and transportation strategies to satisfy time varying demands over a finite horizon, while minimizing system wide cost by taking advantage of quantity discounts in the transportation cost structures. For this purpose, we study the cost effectiveness of restricting the inventory policies to the class of zero-inventory-ordering (ZIO) policies in a single-warehouse multiretailer scenario in which the warehouse serves as a cross-dock facility. In particular, we demonstrate that there exists a ZIO inventory policy whose total inventory and transportation cost is no more than 4/3 (5.6/4.6 if transportation costs are stationary) times the optimal cost. However, finding the best ZIO policy is an NP hard problem as well. Thus, we propose two algorithms to find an effective ZIO policy: An exact algorithm whose running time is polynomial for any fixed number of retailers, and a linear-programming-based heuristic whose effectiveness is demonstrated in a series of computational experiments. Finally, we extend the worst-case results developed in this paper to systems in which the warehouse does hold inventory.

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    File URL: http://dx.doi.org/10.1287/mnsc.48.11.1446.267
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    Bibliographic Info

    Article provided by INFORMS in its journal Management Science.

    Volume (Year): 48 (2002)
    Issue (Month): 11 (November)
    Pages: 1446-1460

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    Handle: RePEc:inm:ormnsc:v:48:y:2002:i:11:p:1446-1460

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    Related research

    Keywords: Approximation Algorithms; Zero-Inventory-Ordering Policies; Inventory; Transportation; Truckload (TL); Less than truckload (LTL);

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    Cited by:
    1. Yu, Min-Chun & Goh, Mark & Lin, Hung-Chung, 2012. "Fuzzy multi-objective vendor selection under lean procurement," European Journal of Operational Research, Elsevier, vol. 219(2), pages 305-311.
    2. Toptal, Aysegül & Bingöl, Safa Onur, 2011. "Transportation pricing of a truckload carrier," European Journal of Operational Research, Elsevier, vol. 214(3), pages 559-567, November.
    3. Ventura, José A. & Valdebenito, Victor A. & Golany, Boaz, 2013. "A dynamic inventory model with supplier selection in a serial supply chain structure," European Journal of Operational Research, Elsevier, vol. 230(2), pages 258-271.
    4. Lee, Dong Joo & Jeong, In-Jae, 2010. "A distributed coordination for a single warehouse-multiple retailer problem under private information," International Journal of Production Economics, Elsevier, vol. 125(1), pages 190-199, May.
    5. Mendoza, Abraham & Ventura, José A., 2008. "Incorporating quantity discounts to the EOQ model with transportation costs," International Journal of Production Economics, Elsevier, vol. 113(2), pages 754-765, June.
    6. Luminiţa Nicolescu & Cristina Galalae & Alexandru Voicu, 2013. "Solving a Supply Chain Management Problem to Near Optimality Using Ant Colony Optimization, in an International Context," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 15(33), pages 8-26, February.

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