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A scaleable projection‐based branch‐and‐cut algorithm for the p‐center problem

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  • Gaar, Elisabeth
  • Sinnl, Markus

Abstract

The p-center problem (pCP) is a fundamental problem in location science, where we are given customer demand points and possible facility locations, and we want to choose p of these locations to open a facility such that the maximum distance of any customer demand point to its closest open facility is minimized. State-of-the-art solution approaches of pCP use its connection to the set cover problem to solve pCP in an iterative fashion by repeatedly solving set cover problems. The classical textbook integer programming (IP) formulation of pCP is usually dismissed due to its size and bad linear programming (LP)-relaxation bounds.

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  • Gaar, Elisabeth & Sinnl, Markus, 2022. "A scaleable projection‐based branch‐and‐cut algorithm for the p‐center problem," European Journal of Operational Research, Elsevier, vol. 303(1), pages 78-98.
    • Handle: RePEc:eee:ejores:v:303:y:2022:i:1:p:78-98
    DOI: 10.1016/j.ejor.2022.02.016
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    References listed on IDEAS

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    6. Rahmaniani, Ragheb & Crainic, Teodor Gabriel & Gendreau, Michel & Rei, Walter, 2017. "The Benders decomposition algorithm: A literature review," European Journal of Operational Research, Elsevier, vol. 259(3), pages 801-817.
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    1. Duran-Mateluna, Cristian & Ales, Zacharie & Elloumi, Sourour, 2023. "An efficient benders decomposition for the p-median problem," European Journal of Operational Research, Elsevier, vol. 308(1), pages 84-96.

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