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A multi-item periodic replenishment policy with full truckloads

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  • Kiesmüller, G.P.
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    Abstract

    In this paper we consider a stochastic multi-item inventory problem. A retailer sells multiple products with stochastic demand and is replenished periodically from a supplier with ample stock. At each order instant it is decided which product to order and how much to order. For the delivery of the products trucks with a finite capacity are available. The dispatched trucks arrive at the retailer after a constant leadtime and with each truck fixed shipping costs are charged independent on the number of units shipped. Additionally, linear holding and backorder costs at the end of a review period are considered. Since fixed transportation costs are high coordination of orders and full truckload shipments can benefit from economies of scale. We propose a dynamic order-up-to policy where initial ordersizes can be reduced as well as enlarged to create full truckloads. We show how to compute the policy parameters and in a detailed numerical study we compare our policy with a lower bound and an uncoordinated periodic replenishment policy. An excellent cost performance of the proposed policy can be observed when average time between two shipments is not too large and fixed shipping costs are high.

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    Bibliographic Info

    Article provided by Elsevier in its journal International Journal of Production Economics.

    Volume (Year): 118 (2009)
    Issue (Month): 1 (March)
    Pages: 275-281

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    Handle: RePEc:eee:proeco:v:118:y:2009:i:1:p:275-281

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    Web page: http://www.elsevier.com/locate/ijpe

    Related research

    Keywords: Inventory Stochastic modelling Coordinated replenishments Joint setup costs;

    References

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    1. Serel, Dogan A. & Dada, Maqbool & Moskowitz, Herbert, 2001. "Sourcing decisions with capacity reservation contracts," European Journal of Operational Research, Elsevier, vol. 131(3), pages 635-648, June.
    2. Carlson, Marvin L & Miltenburg, G John, 1988. "Using the service point model to control large groups of items," Omega, Elsevier, vol. 16(5), pages 481-489.
    3. Joseph L. Balintfy, 1964. "On a Basic Class of Multi-Item Inventory Problems," Management Science, INFORMS, vol. 10(2), pages 287-297, January.
    4. Van Eijs, M. J. G., 1994. "Multi-item inventory systems with joint ordering and transportation decisions," International Journal of Production Economics, Elsevier, vol. 35(1-3), pages 285-292, June.
    5. Melchiors, Philip, 2002. "Calculating can-order policies for the joint replenishment problem by the compensation approach," European Journal of Operational Research, Elsevier, vol. 141(3), pages 587-595, September.
    6. Gerard Cachon, 2001. "Managing a Retailer's Shelf Space, Inventory, and Transportation," Manufacturing & Service Operations Management, INFORMS, vol. 3(3), pages 211-229, July.
    7. Goyal, Suresh K. & Satir, Ahmet T., 1989. "Joint replenishment inventory control: Deterministic and stochastic models," European Journal of Operational Research, Elsevier, vol. 38(1), pages 2-13, January.
    8. Derek R. Atkins & Paul O. Iyogun, 1988. "Periodic Versus "Can-Order" Policies for Coordinated Multi-Item Inventory Systems," Management Science, INFORMS, vol. 34(6), pages 791-796, June.
    9. A. Federgruen & H. Groenevelt & H. C. Tijms, 1984. "Coordinated Replenishments in a Multi-Item Inventory System with Compound Poisson Demands," Management Science, INFORMS, vol. 30(3), pages 344-357, March.
    10. S. Viswanathan, 1997. "Note. Periodic Review (s, S) Policies for Joint Replenishment Inventory Systems," Management Science, INFORMS, vol. 43(10), pages 1447-1454, October.
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    Cited by:
    1. Sancak, Emre & Salman, F. Sibel, 2011. "Multi-item dynamic lot-sizing with delayed transportation policy," International Journal of Production Economics, Elsevier, vol. 131(2), pages 595-603, June.

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