Please use this identifier to cite or link to this item: https://accedacris.ulpgc.es/handle/10553/138541
Title: Modeling and solving an integrated periodic vehicle routing and capacitated facility location problem in the context of solid waste collection
Authors: González, Begoña 
Rossit, Diego
Frutos, Mariano
Méndez Babey, Máximo 
UNESCO Clasification: 120315 Heurística
330807 Eliminación de residuos
332907 Transporte
Keywords: Waste management
Periodic capacitated vehicle routing problem
Capacitated facility location problem
Mixed integer programming
Genetic algorithms, et al
Issue Date: 2025
Journal: Annals of Operations Research 
Abstract: Few activities are as crucial in urban environments as waste management. Mismanagement of waste can cause significant economic, social, and environmental damage. However, waste management is often a complex system to manage and therefore where computational decision-support tools can play a pivotal role in assisting managers to make faster and better decisions. In this sense, this article proposes, on the one hand, a unified optimization model to address two common waste management system optimization problem: the determination of the capacity of waste bins in the collection network and the design and scheduling of collection routes. The integration of these two problems is not usual in the literature since each of them separately is already a major computational challenge. Two improved exact formulations based on mathematical programming and two metaheuristic methods are provided to solve this proposed unified optimization model. It should be noted that the metaheuristics consider a mixed chromosome representation of the solutions combining binary and integer alleles, in order to solve realistic instances of this complex problem. Different parameters of the metaheuristics considered – a Genetic Algorithm and a Simulated Annealing algorithm – have been tested to study which combination of them obtained better results in execution times on the order of that of the exact solvers. The achieved results show that the proposed metaheuristic methods perform efficient on large instances, where exact formulations are not applicable, and offer feasible, high-quality solutions in reasonable calculation times.
URI: https://accedacris.ulpgc.es/handle/10553/138541
ISSN: 0254-5330
DOI: 10.1007/s10479-025-06626-4
Source: Annals of Operations Research [ISSN 0254-5330], v. 348, n. 3, (Mayo 2025)
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