Routing in waste collection: a simulated annealing algorithm for an Argentinean case study

Autores
Rossit, Diego Gabriel; Toncovich, Adrián Andrés; Fermani, Matías
Año de publicación
2021
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The management of the collection of Municipal Solid Waste is a complex task for local governments since it consumes a large portion of their budgets. Thus, the use of computer-aided tools to support decision-making can contribute to improve the efficiency of the system and reduce the associated costs, especially in developing countries, which usually suffer from a shortage of resources. In the present work, a simulated annealing algorithm is proposed to address the problem of designing the routes of waste collection vehicles. The proposed algorithm is compared to a commercial solver based on a mixed-integer programming formulation and two other metaheuristic algorithms, i.e., a state-of-the-art large neighborhood search and a genetic algorithm. The evaluation is carried out on both a well-known benchmark from the literature and real instances of the Argentinean city of Bahía Blanca. The proposed algorithm was able to solve all the instances, having a performance similar to the large neighborhood procedure, while the genetic algorithm showed the worst results. The simulated annealing algorithm was also able to improve the solutions of the solver in many instances of the real dataset.
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: Toncovich, Adrián Andrés. Universidad Nacional del Sur. Departamento de Ingeniería; Argentina
Fil: Fermani, Matías. Universidad Nacional del Sur. Departamento de Ingeniería; Argentina
Materia
MUNICIPAL SOLID WASTE
WASTE COLLECTION
VEHICLE ROUTING PROBLEM
SIMULATED ANNEALING
MIXED-INTEGER PROGRAMMING
LARGE NEIGHBORHOOD SEARCH
GENETIC ALGORITHM
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:11336/151767
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/151767
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Routing in waste collection: a simulated annealing algorithm for an Argentinean case studyRossit, Diego GabrielToncovich, Adrián AndrésFermani, MatíasMUNICIPAL SOLID WASTEWASTE COLLECTIONVEHICLE ROUTING PROBLEMSIMULATED ANNEALINGMIXED-INTEGER PROGRAMMINGLARGE NEIGHBORHOOD SEARCHGENETIC ALGORITHMhttps://purl.org/becyt/ford/2.11https://purl.org/becyt/ford/2The management of the collection of Municipal Solid Waste is a complex task for local governments since it consumes a large portion of their budgets. Thus, the use of computer-aided tools to support decision-making can contribute to improve the efficiency of the system and reduce the associated costs, especially in developing countries, which usually suffer from a shortage of resources. In the present work, a simulated annealing algorithm is proposed to address the problem of designing the routes of waste collection vehicles. The proposed algorithm is compared to a commercial solver based on a mixed-integer programming formulation and two other metaheuristic algorithms, i.e., a state-of-the-art large neighborhood search and a genetic algorithm. The evaluation is carried out on both a well-known benchmark from the literature and real instances of the Argentinean city of Bahía Blanca. The proposed algorithm was able to solve all the instances, having a performance similar to the large neighborhood procedure, while the genetic algorithm showed the worst results. The simulated annealing algorithm was also able to improve the solutions of the solver in many instances of the real dataset.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; ArgentinaFil: Toncovich, Adrián Andrés. Universidad Nacional del Sur. Departamento de Ingeniería; ArgentinaFil: Fermani, Matías. Universidad Nacional del Sur. Departamento de Ingeniería; ArgentinaAmerican Institute of Mathematical Sciences2021-11-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/151767Rossit, Diego Gabriel; Toncovich, Adrián Andrés; Fermani, Matías; Routing in waste collection: a simulated annealing algorithm for an Argentinean case study; American Institute of Mathematical Sciences; Mathematical Biosciences And Engineering; 18; 6; 03-11-2021; 9579-96051547-10631551-0018CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://www.aimspress.com/article/doi/10.3934/mbe.2021470info:eu-repo/semantics/altIdentifier/doi/10.3934/mbe.2021470info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T10:00:26Zoai:ri.conicet.gov.ar:11336/151767instacron: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:34982025-09-03 10:00:26.461CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Routing in waste collection: a simulated annealing algorithm for an Argentinean case study
title Routing in waste collection: a simulated annealing algorithm for an Argentinean case study
spellingShingle Routing in waste collection: a simulated annealing algorithm for an Argentinean case study
Rossit, Diego Gabriel
MUNICIPAL SOLID WASTE
WASTE COLLECTION
VEHICLE ROUTING PROBLEM
SIMULATED ANNEALING
MIXED-INTEGER PROGRAMMING
LARGE NEIGHBORHOOD SEARCH
GENETIC ALGORITHM
title_short Routing in waste collection: a simulated annealing algorithm for an Argentinean case study
title_full Routing in waste collection: a simulated annealing algorithm for an Argentinean case study
title_fullStr Routing in waste collection: a simulated annealing algorithm for an Argentinean case study
title_full_unstemmed Routing in waste collection: a simulated annealing algorithm for an Argentinean case study
title_sort Routing in waste collection: a simulated annealing algorithm for an Argentinean case study
dc.creator.none.fl_str_mv Rossit, Diego Gabriel
Toncovich, Adrián Andrés
Fermani, Matías
author Rossit, Diego Gabriel
author_facet Rossit, Diego Gabriel
Toncovich, Adrián Andrés
Fermani, Matías
author_role author
author2 Toncovich, Adrián Andrés
Fermani, Matías
author2_role author
author
dc.subject.none.fl_str_mv MUNICIPAL SOLID WASTE
WASTE COLLECTION
VEHICLE ROUTING PROBLEM
SIMULATED ANNEALING
MIXED-INTEGER PROGRAMMING
LARGE NEIGHBORHOOD SEARCH
GENETIC ALGORITHM
topic MUNICIPAL SOLID WASTE
WASTE COLLECTION
VEHICLE ROUTING PROBLEM
SIMULATED ANNEALING
MIXED-INTEGER PROGRAMMING
LARGE NEIGHBORHOOD SEARCH
GENETIC ALGORITHM
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.11
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv The management of the collection of Municipal Solid Waste is a complex task for local governments since it consumes a large portion of their budgets. Thus, the use of computer-aided tools to support decision-making can contribute to improve the efficiency of the system and reduce the associated costs, especially in developing countries, which usually suffer from a shortage of resources. In the present work, a simulated annealing algorithm is proposed to address the problem of designing the routes of waste collection vehicles. The proposed algorithm is compared to a commercial solver based on a mixed-integer programming formulation and two other metaheuristic algorithms, i.e., a state-of-the-art large neighborhood search and a genetic algorithm. The evaluation is carried out on both a well-known benchmark from the literature and real instances of the Argentinean city of Bahía Blanca. The proposed algorithm was able to solve all the instances, having a performance similar to the large neighborhood procedure, while the genetic algorithm showed the worst results. The simulated annealing algorithm was also able to improve the solutions of the solver in many instances of the real dataset.
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: Toncovich, Adrián Andrés. Universidad Nacional del Sur. Departamento de Ingeniería; Argentina
Fil: Fermani, Matías. Universidad Nacional del Sur. Departamento de Ingeniería; Argentina
description The management of the collection of Municipal Solid Waste is a complex task for local governments since it consumes a large portion of their budgets. Thus, the use of computer-aided tools to support decision-making can contribute to improve the efficiency of the system and reduce the associated costs, especially in developing countries, which usually suffer from a shortage of resources. In the present work, a simulated annealing algorithm is proposed to address the problem of designing the routes of waste collection vehicles. The proposed algorithm is compared to a commercial solver based on a mixed-integer programming formulation and two other metaheuristic algorithms, i.e., a state-of-the-art large neighborhood search and a genetic algorithm. The evaluation is carried out on both a well-known benchmark from the literature and real instances of the Argentinean city of Bahía Blanca. The proposed algorithm was able to solve all the instances, having a performance similar to the large neighborhood procedure, while the genetic algorithm showed the worst results. The simulated annealing algorithm was also able to improve the solutions of the solver in many instances of the real dataset.
publishDate 2021
dc.date.none.fl_str_mv 2021-11-03
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/11336/151767
Rossit, Diego Gabriel; Toncovich, Adrián Andrés; Fermani, Matías; Routing in waste collection: a simulated annealing algorithm for an Argentinean case study; American Institute of Mathematical Sciences; Mathematical Biosciences And Engineering; 18; 6; 03-11-2021; 9579-9605
1547-1063
1551-0018
CONICET Digital
CONICET
url http://hdl.handle.net/11336/151767
identifier_str_mv Rossit, Diego Gabriel; Toncovich, Adrián Andrés; Fermani, Matías; Routing in waste collection: a simulated annealing algorithm for an Argentinean case study; American Institute of Mathematical Sciences; Mathematical Biosciences And Engineering; 18; 6; 03-11-2021; 9579-9605
1547-1063
1551-0018
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.aimspress.com/article/doi/10.3934/mbe.2021470
info:eu-repo/semantics/altIdentifier/doi/10.3934/mbe.2021470
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 American Institute of Mathematical Sciences
publisher.none.fl_str_mv American Institute of Mathematical Sciences
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
_version_ 1842269637922783232
score 13.13397

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