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A Bilevel Approach to the Facility Location Problem with Customer Preferences Under a Mill Pricing Policy

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  • Herminia I. Calvete

    (Departamento de Métodos Estadísticos, Instituto Universitario de Matemáticas y Aplicaciones (IUMA), Universidad de Zaragoza, Pedro Cerbuna 12, 50009 Zaragoza, Spain)

  • Carmen Galé

    (Departamento de Métodos Estadísticos, Instituto Universitario de Matemáticas y Aplicaciones (IUMA), Universidad de Zaragoza, Pedro Cerbuna 12, 50009 Zaragoza, Spain)

  • Aitor Hernández

    (Departamento de Métodos Estadísticos, Instituto Universitario de Matemáticas y Aplicaciones (IUMA), Universidad de Zaragoza, Pedro Cerbuna 12, 50009 Zaragoza, Spain)

  • José A. Iranzo

    (Departamento de Métodos Estadísticos, Instituto Universitario de Matemáticas y Aplicaciones (IUMA), Universidad de Zaragoza, Pedro Cerbuna 12, 50009 Zaragoza, Spain)

Abstract

This paper addresses the facility location problem under a mill pricing policy, integrating customers’ behavior through the concept of preferences. The problem is modeled as a bilevel optimization problem, where the existence of ties in customers’ preferences can lead to an ill-posed bilevel problem due to the possible existence of multiple optima to the lower-level problem. As the commonly employed optimistic and pessimistic strategies are inadequate for this problem, a specific approach is proposed bearing in mind the customers’ rational behavior. In this work, we propose a novel formulation of the problem as a bilevel model in which each customer faces a lexicographic biobjective problem in which the preference is maximized and the total cost of accessing the selected facility is minimized. This allows for a more accurate representation of customer preferences and the resulting decisions regarding facility location and pricing. To address the complexities of this model, we apply duality theory to the lower-level problems and, ultimately, reformulate the bilevel problem as a single-level mixed-integer optimization problem. This reformulation incorporates big- M constants, for which we provide valid bounds to ensure computational tractability and solution quality. The computational study conducted allows us to assess, on the one hand, the effectiveness of the proposed reformulation to address the bilevel model and, on the other hand, the impact of the length of the customer preference lists and fixed opening cost for facilities on the computational time and the optimal solution.

Suggested Citation

  • Herminia I. Calvete & Carmen Galé & Aitor Hernández & José A. Iranzo, 2024. "A Bilevel Approach to the Facility Location Problem with Customer Preferences Under a Mill Pricing Policy," Mathematics, MDPI, vol. 12(22), pages 1-26, November.
  • Handle: RePEc:gam:jmathe:v:12:y:2024:i:22:p:3459-:d:1514681
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    References listed on IDEAS

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    1. ReVelle, C. S. & Eiselt, H. A., 2005. "Location analysis: A synthesis and survey," European Journal of Operational Research, Elsevier, vol. 165(1), pages 1-19, August.
    2. Klose, Andreas & Drexl, Andreas, 2005. "Facility location models for distribution system design," European Journal of Operational Research, Elsevier, vol. 162(1), pages 4-29, April.
    3. José-Fernando Camacho-Vallejo & Álvaro Eduardo Cordero-Franco & Rosa G. González-Ramírez, 2014. "Solving the Bilevel Facility Location Problem under Preferences by a Stackelberg-Evolutionary Algorithm," Mathematical Problems in Engineering, Hindawi, vol. 2014, pages 1-14, February.
    4. Lin, Yun Hui & Tian, Qingyun, 2023. "Facility location and pricing problem: Discretized mill price and exact algorithms," European Journal of Operational Research, Elsevier, vol. 308(2), pages 568-580.
    5. Marianov, Vladimir & Eiselt, H.A., 2024. "Fifty Years of Location Theory - A Selective Review," European Journal of Operational Research, Elsevier, vol. 318(3), pages 701-718.
    6. Pierre Hanjoul & Pierre Hansen & Dominique Peeters & Jacques-Francois Thisse, 1990. "Uncapacitated Plant Location Under Alternative Spatial Price Policies," Management Science, INFORMS, vol. 36(1), pages 41-57, January.
    7. Casas-Ramírez, Martha-Selene & Camacho-Vallejo, José-Fernando & Martínez-Salazar, Iris-Abril, 2018. "Approximating solutions to a bilevel capacitated facility location problem with customer's patronization toward a list of preferences," Applied Mathematics and Computation, Elsevier, vol. 319(C), pages 369-386.
    8. Benoît Colson & Patrice Marcotte & Gilles Savard, 2007. "An overview of bilevel optimization," Annals of Operations Research, Springer, vol. 153(1), pages 235-256, September.
    9. Hanjoul, Pierre & Peeters, Dominique, 1987. "A facility location problem with clients' preference orderings," Regional Science and Urban Economics, Elsevier, vol. 17(3), pages 451-473, August.
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