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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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    Cited by:

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    4. Lim, Gino J. & Sonmez, Ayse Durukan, 2013. "γ-Robust facility relocation problem," European Journal of Operational Research, Elsevier, vol. 229(1), pages 67-74.
    5. Amir Hossein Sadeghi & Ziyuan Sun & Amirreza Sahebi-Fakhrabad & Hamid Arzani & Robert Handfield, 2023. "A Mixed-Integer Linear Formulation for a Dynamic Modified Stochastic p-Median Problem in a Competitive Supply Chain Network Design," Logistics, MDPI, vol. 7(1), pages 1-24, March.
    6. 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.
    7. 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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    9. Bruno, Giuseppe & Diglio, Antonio & Piccolo, Carmela & Cannavacciuolo, Lorella, 2019. "Territorial reorganization of regional blood management systems: Evidences from an Italian case study," Omega, Elsevier, vol. 89(C), pages 54-70.

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