Modeling and solving an integrated periodic vehicle routing and capacitated facility location problem in the context of solid waste collection

Autores
González, Begoña; Rossit, Diego Gabriel; Frutos, Mariano; Méndez, Máximo
Año de publicación
2025
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
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.
Fil: González, Begoña. Universidad de Las Palmas de Gran Canaria; España
Fil: Rossit, Diego Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería; Argentina
Fil: Frutos, Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Económicas y Sociales del Sur. Universidad Nacional del Sur. Departamento de Economía. Instituto de Investigaciones Económicas y Sociales del Sur; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería; Argentina
Fil: Méndez, Máximo. Universidad de Las Palmas de Gran Canaria; España
Materia
WASTE MANAGEMENT
PERIODIC CAPACITATED VEHICLE ROUTING PROBLEM
CAPACITATED FACILITY LOCATION PROBLEM
MIXED INTEGER PROGRAMMING
GENETIC ALGORITHMS
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/263958
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/263958
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repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Modeling and solving an integrated periodic vehicle routing and capacitated facility location problem in the context of solid waste collectionGonzález, BegoñaRossit, Diego GabrielFrutos, MarianoMéndez, MáximoWASTE MANAGEMENTPERIODIC CAPACITATED VEHICLE ROUTING PROBLEMCAPACITATED FACILITY LOCATION PROBLEMMIXED INTEGER PROGRAMMINGGENETIC ALGORITHMShttps://purl.org/becyt/ford/2.11https://purl.org/becyt/ford/2Few 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.Fil: González, Begoña. Universidad de Las Palmas de Gran Canaria; EspañaFil: Rossit, Diego Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería; ArgentinaFil: Frutos, Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Económicas y Sociales del Sur. Universidad Nacional del Sur. Departamento de Economía. Instituto de Investigaciones Económicas y Sociales del Sur; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería; ArgentinaFil: Méndez, Máximo. Universidad de Las Palmas de Gran Canaria; EspañaSpringer2025-05-18info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/263958González, Begoña; Rossit, Diego Gabriel; Frutos, Mariano; Méndez, Máximo; Modeling and solving an integrated periodic vehicle routing and capacitated facility location problem in the context of solid waste collection; Springer; Annals Of Operations Research; 18-5-2025; 1-370254-5330CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1007/s10479-025-06626-4info:eu-repo/semantics/altIdentifier/url/https://link.springer.com/article/10.1007/s10479-025-06626-4info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-10T13:17:43Zoai:ri.conicet.gov.ar:11336/263958instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-10 13:17:44.121CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Modeling and solving an integrated periodic vehicle routing and capacitated facility location problem in the context of solid waste collection
title Modeling and solving an integrated periodic vehicle routing and capacitated facility location problem in the context of solid waste collection
spellingShingle Modeling and solving an integrated periodic vehicle routing and capacitated facility location problem in the context of solid waste collection
González, Begoña
WASTE MANAGEMENT
PERIODIC CAPACITATED VEHICLE ROUTING PROBLEM
CAPACITATED FACILITY LOCATION PROBLEM
MIXED INTEGER PROGRAMMING
GENETIC ALGORITHMS
title_short Modeling and solving an integrated periodic vehicle routing and capacitated facility location problem in the context of solid waste collection
title_full Modeling and solving an integrated periodic vehicle routing and capacitated facility location problem in the context of solid waste collection
title_fullStr Modeling and solving an integrated periodic vehicle routing and capacitated facility location problem in the context of solid waste collection
title_full_unstemmed Modeling and solving an integrated periodic vehicle routing and capacitated facility location problem in the context of solid waste collection
title_sort Modeling and solving an integrated periodic vehicle routing and capacitated facility location problem in the context of solid waste collection
dc.creator.none.fl_str_mv González, Begoña
Rossit, Diego Gabriel
Frutos, Mariano
Méndez, Máximo
author González, Begoña
author_facet González, Begoña
Rossit, Diego Gabriel
Frutos, Mariano
Méndez, Máximo
author_role author
author2 Rossit, Diego Gabriel
Frutos, Mariano
Méndez, Máximo
author2_role author
author
author
dc.subject.none.fl_str_mv WASTE MANAGEMENT
PERIODIC CAPACITATED VEHICLE ROUTING PROBLEM
CAPACITATED FACILITY LOCATION PROBLEM
MIXED INTEGER PROGRAMMING
GENETIC ALGORITHMS
topic WASTE MANAGEMENT
PERIODIC CAPACITATED VEHICLE ROUTING PROBLEM
CAPACITATED FACILITY LOCATION PROBLEM
MIXED INTEGER PROGRAMMING
GENETIC ALGORITHMS
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.11
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv 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.
Fil: González, Begoña. Universidad de Las Palmas de Gran Canaria; España
Fil: Rossit, Diego Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería; Argentina
Fil: Frutos, Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Económicas y Sociales del Sur. Universidad Nacional del Sur. Departamento de Economía. Instituto de Investigaciones Económicas y Sociales del Sur; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería; Argentina
Fil: Méndez, Máximo. Universidad de Las Palmas de Gran Canaria; España
description 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.
publishDate 2025
dc.date.none.fl_str_mv 2025-05-18
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/263958
González, Begoña; Rossit, Diego Gabriel; Frutos, Mariano; Méndez, Máximo; Modeling and solving an integrated periodic vehicle routing and capacitated facility location problem in the context of solid waste collection; Springer; Annals Of Operations Research; 18-5-2025; 1-37
0254-5330
CONICET Digital
CONICET
url http://hdl.handle.net/11336/263958
identifier_str_mv González, Begoña; Rossit, Diego Gabriel; Frutos, Mariano; Méndez, Máximo; Modeling and solving an integrated periodic vehicle routing and capacitated facility location problem in the context of solid waste collection; Springer; Annals Of Operations Research; 18-5-2025; 1-37
0254-5330
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1007/s10479-025-06626-4
info:eu-repo/semantics/altIdentifier/url/https://link.springer.com/article/10.1007/s10479-025-06626-4
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 12.993085

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