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Uncapacitated and Capacitated Facility Location Problems

In: Foundations of Location Analysis

Author

Listed:
  • Vedat Verter

    (McGill University)

Abstract

The uncapacitated facility location problem (UFLP) involves locating an undetermined number of facilities to minimize the sum of the (annualized) fixed setup costs and the variable costs of serving the market demand from these facilities. UFLP is also known as the “simple” facility location problem SFLP, where both the alternative facility locations and the customer zones are considered discrete points on a plane or a road network. This assumes that the alternative sites have been predetermined and the demand in each customer zone is concentrated at the point representing that region. UFLP focuses on the production and distribution of a single commodity over a single time period (e.g., one year that is representative of the firm’s long-run demand and cost structure), during which the demand is assumed to be known with certainty. The distinguishing feature of this basic discrete location problem, however, is the decision maker’s ability to determine the size of each facility without any budgetary, technological, or physical restrictions. Krarup and Pruzan (1983) provided a comprehensive survey of the early literature on UFLP, including its solution properties. By demonstrating the relationships between UFLP and the set packing-covering-partitioning problems, they established its NP-completeness.

Suggested Citation

  • Vedat Verter, 2011. "Uncapacitated and Capacitated Facility Location Problems," International Series in Operations Research & Management Science, in: H. A. Eiselt & Vladimir Marianov (ed.), Foundations of Location Analysis, chapter 0, pages 25-37, Springer.
    • Handle: RePEc:spr:isochp:978-1-4419-7572-0_2
    DOI: 10.1007/978-1-4419-7572-0_2
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    Citations

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    Cited by:

    1. Álvarez-Miranda, Eduardo & Fernández, Elena & Ljubić, Ivana, 2015. "The recoverable robust facility location problem," Transportation Research Part B: Methodological, Elsevier, vol. 79(C), pages 93-120.
    2. Galli, Laura & Letchford, Adam N. & Miller, Sebastian J., 2018. "New valid inequalities and facets for the Simple Plant Location Problem," European Journal of Operational Research, Elsevier, vol. 269(3), pages 824-833.
    3. Fabian Eckert & Costas Arkolakis, 2017. "Combinatorial Discrete Choice," 2017 Meeting Papers 249, Society for Economic Dynamics.
    4. Marianov, Vladimir & Eiselt, H.A. & Lüer-Villagra, Armin, 2018. "Effects of multipurpose shopping trips on retail store location in a duopoly," European Journal of Operational Research, Elsevier, vol. 269(2), pages 782-792.
    5. Christensen, Tue Rauff Lind & Klose, Andreas, 2021. "A fast exact method for the capacitated facility location problem with differentiable convex production costs," European Journal of Operational Research, Elsevier, vol. 292(3), pages 855-868.
    6. Saif, Ahmed & Elhedhli, Samir, 2016. "Cold supply chain design with environmental considerations: A simulation-optimization approach," European Journal of Operational Research, Elsevier, vol. 251(1), pages 274-287.
    7. Letchford, Adam N. & Miller, Sebastian J., 2014. "An aggressive reduction scheme for the simple plant location problem," European Journal of Operational Research, Elsevier, vol. 234(3), pages 674-682.
    8. Jesica Armas & Angel A. Juan & Joan M. Marquès & João Pedro Pedroso, 2017. "Solving the deterministic and stochastic uncapacitated facility location problem: from a heuristic to a simheuristic," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(10), pages 1161-1176, October.
    9. Matteo Fischetti & Ivana Ljubić & Markus Sinnl, 2017. "Redesigning Benders Decomposition for Large-Scale Facility Location," Management Science, INFORMS, vol. 63(7), pages 2146-2162, July.
    10. Wu, Shanhua & Yang, Zhongzhen, 2018. "Optimizing location of manufacturing industries in the context of economic globalization: A bi-level model based approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 501(C), pages 327-337.
    11. Melendez, Kevin A. & Das, Tapas K. & Kwon, Changhyun, 2020. "Optimal operation of a system of charging hubs and a fleet of shared autonomous electric vehicles," Applied Energy, Elsevier, vol. 279(C).
    12. Monabbati, Ehsan & Kakhki, Hossein Taghizadeh, 2015. "On a class of subadditive duals for the uncapacitated facility location problem," Applied Mathematics and Computation, Elsevier, vol. 251(C), pages 118-131.
    13. Holzapfel, Andreas & Potoczki, Tobias & Kuhn, Heinrich, 2023. "Designing the breadth and depth of distribution networks in the retail trade," International Journal of Production Economics, Elsevier, vol. 257(C).
    14. Liming Yao & Zhongwen Xu & Ziqiang Zeng, 2020. "A Soft‐Path Solution to Risk Reduction by Modeling Medical Waste Disposal Center Location‐Allocation Optimization," Risk Analysis, John Wiley & Sons, vol. 40(9), pages 1863-1886, September.

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