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Risk-Pooling Along a Fixed Delivery Route Using a Dynamic Inventory-Allocation Policy

Author

Listed:
  • Ashok Kumar

    (Department of Management, Eberhard Center, Room 510, Grand Valley State University, Grand Rapids, Michigan 49504)

  • Leroy B. Schwarz

    (Krannert Graduate School of Management, Purdue University, West Lafayette, Indiana 47907)

  • James E. Ward

    (Krannert Graduate School of Management, Purdue University, West Lafayette, Indiana 47907)

Abstract

This paper examines static and dynamic policies for replenishing and allocating inventories amongst N retailers located along a fixed delivery route. Each retailer faces independent, normally-distributed period demand and incurs a proportional holding or backorder cost on end-of-period net-inventory. A warehouse places a system-replenishment order every m periods which is received after a fixed leadtime of T periods. Immediately upon receipt, a delivery vehicle leaves the warehouse with the system-replenishment quantity and travels to the retailers along a fixed route with fixed leadtimes between successive retailers. The warehouse holds no inventory. Under the "static" policy, allocations are determined for all retailers simultaneously at the moment the delivery vehicle leaves the warehouse. Under the "dynamic" policy, allocations are determined sequentially upon arrival of the delivery vehicle at each retailer. Our major analytical results, under appropriate dynamic (static) allocation assumptions, are: (1) optimal allocations under each policy involve bringing each retailer's "normalized-inventory" to a corresponing "normalized" system inventory; (2) optimal system replenishments are base-stock policies; (3) the minimum expected cost per cycle of dynamic (static) policy can be derived from an equivalent dynamic (static) composite retailer. Given this, we prove that the "risk-pooling incentive"---a simple measure of the benefit from adopting dynamic allocation policies---is always positive. Our simulation tests confirm that dynamic allocation policies yield lower costs than static policies, regardless of whether or not their respective allocation assumptions are valid. However, the magnitude of the cost savings is very sensitive to some system parameters.

Suggested Citation

  • Ashok Kumar & Leroy B. Schwarz & James E. Ward, 1995. "Risk-Pooling Along a Fixed Delivery Route Using a Dynamic Inventory-Allocation Policy," Management Science, INFORMS, vol. 41(2), pages 344-362, February.
  • Handle: RePEc:inm:ormnsc:v:41:y:1995:i:2:p:344-362
    DOI: 10.1287/mnsc.41.2.344
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    Citations

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    Cited by:

    1. Bosung Kim & Sang Won Kim & Seyed M. R. Iravani & Kun Soo Park, 2021. "Simple Mechanisms for Sequential Capacity Allocations," Production and Operations Management, Production and Operations Management Society, vol. 30(9), pages 2925-2943, September.
    2. Nair, Anand & Closs, David J., 2006. "An examination of the impact of coordinating supply chain policies and price markdowns on short lifecycle product retail performance," International Journal of Production Economics, Elsevier, vol. 102(2), pages 379-392, August.
    3. Patrick Jaillet & Jonathan F. Bard & Liu Huang & Moshe Dror, 2002. "Delivery Cost Approximations for Inventory Routing Problems in a Rolling Horizon Framework," Transportation Science, INFORMS, vol. 36(3), pages 292-300, August.
    4. Ki Ling Cheung & Hau L. Lee, 2002. "The Inventory Benefit of Shipment Coordination and Stock Rebalancing in a Supply Chain," Management Science, INFORMS, vol. 48(2), pages 300-306, February.
    5. Martin I. Reiman & Rodrigo Rubio & Lawrence M. Wein, 1999. "Heavy Traffic Analysis of the Dynamic Stochastic Inventory-Routing Problem," Transportation Science, INFORMS, vol. 33(4), pages 361-380, November.
    6. Zhai, Xin & Ward, James E. & Schwarz, Leroy B., 2011. "Coordinating a one-warehouse N-retailer distribution system under retailer-reporting," International Journal of Production Economics, Elsevier, vol. 134(1), pages 204-211, November.
    7. Johan Marklund & Kaj Rosling, 2012. "Lower Bounds and Heuristics for Supply Chain Stock Allocation," Operations Research, INFORMS, vol. 60(1), pages 92-105, February.
    8. Bendoly, Elliot & Blocher, Doug & Bretthauer, Kurt M. & Venkataramanan, M.A., 2007. "Service and cost benefits through clicks-and-mortar integration: Implications for the centralization/decentralization debate," European Journal of Operational Research, Elsevier, vol. 180(1), pages 426-442, July.
    9. R. L. Francis & T. J. Lowe & Arie Tamir, 2000. "Aggregation Error Bounds for a Class of Location Models," Operations Research, INFORMS, vol. 48(2), pages 294-307, April.
    10. Qing Li & Xiaoli Wu & Ki Ling Cheung, 2009. "Optimal Policies for Inventory Systems with Separate Delivery-Request and Order-Quantity Decisions," Operations Research, INFORMS, vol. 57(3), pages 626-636, June.
    11. Leroy B. Schwarz & James E. Ward & Xin Zhai, 2006. "On the Interactions Between Routing and Inventory-Management Policies in a One-Warehouse N-Retailer Distribution System," Manufacturing & Service Operations Management, INFORMS, vol. 8(3), pages 253-272, September.
    12. Amin Abbasi-Pooya & Michael T. Lash, 2024. "The third party logistics provider freight management problem: a framework and deep reinforcement learning approach," Annals of Operations Research, Springer, vol. 339(1), pages 965-1024, August.
    13. Agrawal, Vipul & Chao, Xiuli & Seshadri, Sridhar, 2004. "Dynamic balancing of inventory in supply chains," European Journal of Operational Research, Elsevier, vol. 159(2), pages 296-317, December.
    14. Ernst, Ricardo & Kamrad, Bardia, 1997. "Allocation of warehouse inventory with electronic data interchange and fixed order intervals," European Journal of Operational Research, Elsevier, vol. 103(1), pages 117-128, November.
    15. Yu, Yugang & Chen, Haoxun & Chu, Feng, 2008. "A new model and hybrid approach for large scale inventory routing problems," European Journal of Operational Research, Elsevier, vol. 189(3), pages 1022-1040, September.
    16. Huang, Huei-Chuen & Song, Haiqing, 2010. "Modified base-stock policies for semiconductor production system with dependent yield rates," European Journal of Operational Research, Elsevier, vol. 207(1), pages 206-217, November.
    17. Sonntag, Danja R. & Schrotenboer, Albert H. & Kiesmüller, Gudrun P., 2023. "Stochastic inventory routing with time-based shipment consolidation," European Journal of Operational Research, Elsevier, vol. 306(3), pages 1186-1201.
    18. Robert W. Lien & Seyed M. R. Iravani & Karen R. Smilowitz, 2014. "Sequential Resource Allocation for Nonprofit Operations," Operations Research, INFORMS, vol. 62(2), pages 301-317, April.

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