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A decomposition approach for facility location and relocation problem with uncertain number of future facilities

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  • Sonmez, Ayse Durukan
  • Lim, Gino J.

Abstract

In this paper, we discuss two challenges of long term facility location problem that occur simultaneously; future demand change and uncertain number of future facilities. We introduce a mathematical model that minimizes the initial and expected future weighted travel distance of customers. Our model allows relocation for the future instances by closing some of the facilities that were located initially and opening new ones, without exceeding a given budget. We present an integer programming formulation of the problem and develop a decomposition algorithm that can produce near optimal solutions in a fast manner. We compare the performance of our mathematical model against another method adapted from the literature and perform sensitivity analysis. We present numerical results that compare the performance of the proposed decomposition algorithm against the exact algorithm for the problem.

Suggested Citation

  • Sonmez, Ayse Durukan & Lim, Gino J., 2012. "A decomposition approach for facility location and relocation problem with uncertain number of future facilities," European Journal of Operational Research, Elsevier, vol. 218(2), pages 327-338.
  • Handle: RePEc:eee:ejores:v:218:y:2012:i:2:p:327-338
    DOI: 10.1016/j.ejor.2011.10.028
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    References listed on IDEAS

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    1. Current, John & Ratick, Samuel & ReVelle, Charles, 1998. "Dynamic facility location when the total number of facilities is uncertain: A decision analysis approach," European Journal of Operational Research, Elsevier, vol. 110(3), pages 597-609, November.
    2. Owen, Susan Hesse & Daskin, Mark S., 1998. "Strategic facility location: A review," European Journal of Operational Research, Elsevier, vol. 111(3), pages 423-447, December.
    3. George O. Wesolowsky & William G. Truscott, 1975. "The Multiperiod Location-Allocation Problem with Relocation of Facilities," Management Science, INFORMS, vol. 22(1), pages 57-65, September.
    4. Berman, Oded & Drezner, Zvi, 2008. "The p-median problem under uncertainty," European Journal of Operational Research, Elsevier, vol. 189(1), pages 19-30, August.
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    Cited by:

    1. Günther Zäpfel & Michael Bögl, 2016. "An adaptive structure of a hub-and-spoke system with direct and depot shipments in the case of volatile demand over time," Journal of Business Economics, Springer, vol. 86(7), pages 697-721, October.
    2. Lim, Gino J. & Sonmez, Ayse Durukan, 2013. "γ-Robust facility relocation problem," European Journal of Operational Research, Elsevier, vol. 229(1), pages 67-74.
    3. Guerriero, Francesca & Miglionico, Giovanna & Olivito, Filomena, 2016. "Location and reorganization problems: The Calabrian health care system case," European Journal of Operational Research, Elsevier, vol. 250(3), pages 939-954.
    4. Lei, Chao & Lin, Wei-Hua & Miao, Lixin, 2014. "A multicut L-shaped based algorithm to solve a stochastic programming model for the mobile facility routing and scheduling problem," European Journal of Operational Research, Elsevier, vol. 238(3), pages 699-710.

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    Keywords

    Facility location; Uncertainty; p-Median;

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