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Combining state-of-the-art row generation methods for the competitive facility location problem with multinomial logit choice rule

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  • Méndez-Vogel, Gonzalo
  • Marianov, Vladimir
  • Lüer-Villagra, Armin

Abstract

The competitive facility location problem, in which customers are assumed to use the multinomial logit rule to choose where to purchase, has gained increasing attention in the location field. In 2014, a comparison between the most successful exact solution methods at that time was published. These were based on the linearization of the logit formula. In the ten years following that comparison, important advancements have been made in finding exact solutions to the problem based on row generation methods. Different types of cuts have been proposed together with two approaches of using them. We introduce the three articles that represent the state-of-the-art, and we combine the cuts and methods presented in these articles to explore new approaches and find the best exact methods using an empirical approach to the most popular test instances. The best methods obtained have not been presented in the literature so far. We also discuss some improvement paths.

Suggested Citation

  • Méndez-Vogel, Gonzalo & Marianov, Vladimir & Lüer-Villagra, Armin, 2025. "Combining state-of-the-art row generation methods for the competitive facility location problem with multinomial logit choice rule," Omega, Elsevier, vol. 136(C).
  • Handle: RePEc:eee:jomega:v:136:y:2025:i:c:s0305048325000659
    DOI: 10.1016/j.omega.2025.103339
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    References listed on IDEAS

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    1. Lin, Yun Hui & Tian, Qingyun, 2021. "Branch-and-cut approach based on generalized benders decomposition for facility location with limited choice rule," European Journal of Operational Research, Elsevier, vol. 293(1), pages 109-119.
    2. Mai, Tien & Lodi, Andrea, 2020. "A multicut outer-approximation approach for competitive facility location under random utilities," European Journal of Operational Research, Elsevier, vol. 284(3), pages 874-881.
    3. Aros-Vera, Felipe & Marianov, Vladimir & Mitchell, John E., 2013. "p-Hub approach for the optimal park-and-ride facility location problem," European Journal of Operational Research, Elsevier, vol. 226(2), pages 277-285.
    4. Dam, Tien Thanh & Ta, Thuy Anh & Mai, Tien, 2022. "Submodularity and local search approaches for maximum capture problems under generalized extreme value models," European Journal of Operational Research, Elsevier, vol. 300(3), pages 953-965.
    5. Ralf Krohn & Sven Müller & Knut Haase, 2021. "Preventive healthcare facility location planning with quality-conscious clients," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(1), pages 59-87, March.
    6. Ljubić, Ivana & Moreno, Eduardo, 2018. "Outer approximation and submodular cuts for maximum capture facility location problems with random utilities," European Journal of Operational Research, Elsevier, vol. 266(1), pages 46-56.
    7. Haase, Knut & Müller, Sven, 2014. "A comparison of linear reformulations for multinomial logit choice probabilities in facility location models," European Journal of Operational Research, Elsevier, vol. 232(3), pages 689-691.
    8. Dam, Tien Thanh & Ta, Thuy Anh & Mai, Tien, 2023. "Robust maximum capture facility location under random utility maximization models," European Journal of Operational Research, Elsevier, vol. 310(3), pages 1128-1150.
    9. Benati, Stefano & Hansen, Pierre, 2002. "The maximum capture problem with random utilities: Problem formulation and algorithms," European Journal of Operational Research, Elsevier, vol. 143(3), pages 518-530, December.
    10. Freire, Alexandre S. & Moreno, Eduardo & Yushimito, Wilfredo F., 2016. "A branch-and-bound algorithm for the maximum capture problem with random utilities," European Journal of Operational Research, Elsevier, vol. 252(1), pages 204-212.
    11. Nemhauser, G.L. & Wolsey, L.A., 1981. "Maximizing submodular set functions: formulations and analysis of algorithms," LIDAM Reprints CORE 455, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    12. Méndez-Vogel, Gonzalo & Marianov, Vladimir & Lüer-Villagra, Armin, 2023. "The follower competitive facility location problem under the nested logit choice rule," European Journal of Operational Research, Elsevier, vol. 310(2), pages 834-846.
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