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

Calvete, Herminia I. (Universidad de Zaragoza) ; Galé, Carmen (Universidad de Zaragoza) ; Hernández, Aitor (Universidad de Zaragoza) ; Iranzo, José A. (Universidad de Zaragoza)

Resumen: 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.

Idioma: Inglés

DOI: 10.3390/math12223459

Año: 2024

Publicado en: Mathematics 12, 22 (2024), 3459 [25 pp.]
ISSN: 2227-7390

Factor impacto JCR: 2.2 (2024)

Categ. JCR: MATHEMATICS rank: 29 / 483 = 0.06 (2024) - Q1 - T1

Factor impacto SCIMAGO: 0.498 - Engineering (miscellaneous) (Q2) - Mathematics (miscellaneous) (Q2) - Computer Science (miscellaneous) (Q2)

Financiación: info:eu-repo/grantAgreement/ES/DGA/E41-23R
Financiación: info:eu-repo/grantAgreement/ES/MICINN/PID2022-139543OB-C43
Financiación: info:eu-repo/grantAgreement/EUR/MICINN/TED2021-130961B-I00

Tipo y forma: Article (Published version)

Área (Departamento): Área Estadís. Investig. Opera. (Dpto. Métodos Estadísticos)