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A coordinated location-inventory model


  • Berman, Oded
  • Krass, Dmitry
  • Tajbakhsh, M. Mahdi


We consider a coordinated location-inventory model where distribution centers (DCs) follow a periodic-review (R,S) inventory policy and system coordination is achieved by choosing review intervals at the DCs from a menu of permissible choices. We introduce two types of coordination: partial coordination where each DC may choose its own review interval from the menu, and full coordination where all the DCs have an identical review interval. While full coordination increases the location and inventory costs, it likely reduces the overall costs of running the system (when the operational costs such as delivery scheduling are taken into account). The problem is to determine the location of the DCs to be opened, the assignment of retailers to DCs, and the inventory policy parameters at the DCs such that the total system-wide cost is minimized. The model is formulated as a nonlinear integer-programming problem and a Lagrangian relaxation algorithm is proposed to solve it. Computational results show that the proposed algorithm is very efficient. The results of our computational experiments and case study suggest that the location and inventory cost increase due to full coordination, when compared to partial coordination, is not significant. Thus, full coordination, while enhancing the practicality of the model, is economically justifiable.

Suggested Citation

  • Berman, Oded & Krass, Dmitry & Tajbakhsh, M. Mahdi, 2012. "A coordinated location-inventory model," European Journal of Operational Research, Elsevier, vol. 217(3), pages 500-508.
  • Handle: RePEc:eee:ejores:v:217:y:2012:i:3:p:500-508
    DOI: 10.1016/j.ejor.2011.09.039

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    References listed on IDEAS

    1. Zuo-Jun Max Shen & Mark S. Daskin, 2005. "Trade-offs Between Customer Service and Cost in Integrated Supply Chain Design," Manufacturing & Service Operations Management, INFORMS, vol. 7(3), pages 188-207, September.
    2. Snyder, Lawrence V. & Daskin, Mark S. & Teo, Chung-Piaw, 2007. "The stochastic location model with risk pooling," European Journal of Operational Research, Elsevier, vol. 179(3), pages 1221-1238, June.
    3. Marshall L. Fisher, 1981. "The Lagrangian Relaxation Method for Solving Integer Programming Problems," Management Science, INFORMS, vol. 27(1), pages 1-18, January.
    4. Gary D. Eppen, 1979. "Note--Effects of Centralization on Expected Costs in a Multi-Location Newsboy Problem," Management Science, INFORMS, vol. 25(5), pages 498-501, May.
    5. Mozart Menezes & O. Berman & D. Krass, 2007. "Facility Reliability Issues in Network p-Median Problems: Strategic Centralization and Co-location Effects," Post-Print halshs-00170396, HAL.
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    Cited by:

    1. Gülpınar, Nalan & Pachamanova, Dessislava & Çanakoğlu, Ethem, 2013. "Robust strategies for facility location under uncertainty," European Journal of Operational Research, Elsevier, vol. 225(1), pages 21-35.
    2. repec:eee:ejores:v:266:y:2018:i:1:p:72-87 is not listed on IDEAS
    3. Zhang, Zhi-Hai & Unnikrishnan, Avinash, 2016. "A coordinated location-inventory problem in closed-loop supply chain," Transportation Research Part B: Methodological, Elsevier, vol. 89(C), pages 127-148.
    4. Schuster Puga, Matías & Tancrez, Jean-Sébastien, 2017. "A heuristic algorithm for solving large location–inventory problems with demand uncertainty," European Journal of Operational Research, Elsevier, vol. 259(2), pages 413-423.
    5. repec:eee:ejores:v:264:y:2018:i:3:p:948-966 is not listed on IDEAS


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