A Forward-Backward Simheuristic for the Stochastic Capacitated Dispersion Problem
Gómez González, Juan Francisco (Universitat Politècnica de València)
Martínez-Gavara, Anna (Universitat de València)
Panadero, Javier (Universitat Autònoma de Barcelona. Departament d'Arquitectura de Computadors i Sistemes Operatius)
Juan, Ángel A (Universitat Politècnica de València)
Martí, Rafael (Universitat de València)

Fecha:	2024
Resumen:	In an effort to balance the distribution of services across a given territory, dispersion and diversity models typically aim to maximize the minimum distance between any pair of facilities. Specifically, in the capacitated dispersion problem (CDP), each facility has an associated capacity or level of service, and the objective is to select a set of facilities so that the minimum distance between any pair of them (dispersion) is maximized, while ensuring a user-defined level of service. This problem can be formulated as a linear integer model, where the sum of the capacities of the selected facilities must match or exceed the total demand in the network. Real-life applications often necessitate considering the levels of uncertainty affecting the capacity of the nodes. Failure to account for this uncertainty could lead to low-quality or infeasible solutions in practical scenarios. However, research addressing the stochastic version of the CDP is scarce. This paper introduces two models for the CDP with stochastic capacities, incorporating soft constraints and penalty costs for violating the total capacity constraint. The first model includes a probabilistic constraint to ensure the required level of service with a certain probability, while the second model introduces a soft constraint with penalty costs for violations. To solve both variants of the model, a forward-backward simheuristic algorithm is proposed. Our approach combines a metaheuristic algorithm with Monte Carlo simulation, enabling the efficient handling of the random behavior of node capacities and obtaining reliable solutions regardless of their probability distribution.
Ayudas:	European Commission 101096405 European Commission 101092612 Agencia Estatal de Investigación PID2022-138860NB-I00 Agencia Estatal de Investigación RED2022-134703-T Agencia Estatal de Investigación PID2021-125709OB-C21
Derechos:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Lengua:	Anglès
Documento:	Article ; recerca ; Versió publicada
Materia:	Dispersion problem ; Metaheuristics ; Simulation ; Stochastic optimization problems
Publicado en:	Mathematics, Vol. 12, Issue 6 (March 2024) , art. 909, ISSN 2227-7390

DOI: 10.3390/math12060909

22 p, 717.7 KB

El registro aparece en las colecciones:
Artículos > Artículos de investigación
Artículos > Artículos publicados