Solving a multi-objective manufacturing cell scheduling problem with the consideration of warehouses using a simulated annealing based procedure

Autores
Toncovich, Adrián Andrés; Rossit, Daniel Alejandro; Frutos, Mariano; Rossit, Diego Gabriel
Año de publicación
2019
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The competition manufacturing companies face has driven the development of novel and efficient methods that enhance the decision making process. In this work, a specific flow shop scheduling problem of practical interest in the industry is presented and formalized using a mathematical programming model. The problem considers a manufacturing system arranged as a work cell that takes into account the transport operations of raw material and final products between the manufacturing cell and warehouses. For solving this problem, we present a multiobjective metaheuristic strategy based on simulated annealing, the Pareto Archived Simulated Annealing (PASA). We tested this strategy on two kinds of benchmark problem sets proposed by the authors. The first group is composed by small-sized problems. On these tests, PASA was able to obtain optimal or near-optimal solutions in significantly short computing times. In order to complete the analysis, we compared these results to the exact Pareto front of the instances obtained with augmented ε-constraint method. Then, we also tested the algorithm in a set of larger problems to evaluate its performance in more extensive search spaces. We performed this assessment through an analysis of the hypervolume metric. Both sets of tests showed the competitiveness of the Pareto Archived Simulated Annealing to efficiently solve this problem and obtain good quality solutions while using reasonable computational resources.
Fil: Toncovich, Adrián Andrés. Universidad Nacional del Sur. Departamento de Ingeniería; Argentina
Fil: Rossit, Daniel Alejandro. 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: Rossit, Diego Gabriel. 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
Materia
ANNEALING
FLOW-SHOP
MULTI-OBJECTIVE OPTIMIZATION
PARETO ARCHIVED SIMULATED
PRODUCTION SCHEDULING
WAREHOUSES
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/112474
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/112474
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Solving a multi-objective manufacturing cell scheduling problem with the consideration of warehouses using a simulated annealing based procedureToncovich, Adrián AndrésRossit, Daniel AlejandroFrutos, MarianoRossit, Diego GabrielANNEALINGFLOW-SHOPMULTI-OBJECTIVE OPTIMIZATIONPARETO ARCHIVED SIMULATEDPRODUCTION SCHEDULINGWAREHOUSEShttps://purl.org/becyt/ford/2.11https://purl.org/becyt/ford/2The competition manufacturing companies face has driven the development of novel and efficient methods that enhance the decision making process. In this work, a specific flow shop scheduling problem of practical interest in the industry is presented and formalized using a mathematical programming model. The problem considers a manufacturing system arranged as a work cell that takes into account the transport operations of raw material and final products between the manufacturing cell and warehouses. For solving this problem, we present a multiobjective metaheuristic strategy based on simulated annealing, the Pareto Archived Simulated Annealing (PASA). We tested this strategy on two kinds of benchmark problem sets proposed by the authors. The first group is composed by small-sized problems. On these tests, PASA was able to obtain optimal or near-optimal solutions in significantly short computing times. In order to complete the analysis, we compared these results to the exact Pareto front of the instances obtained with augmented ε-constraint method. Then, we also tested the algorithm in a set of larger problems to evaluate its performance in more extensive search spaces. We performed this assessment through an analysis of the hypervolume metric. Both sets of tests showed the competitiveness of the Pareto Archived Simulated Annealing to efficiently solve this problem and obtain good quality solutions while using reasonable computational resources.Fil: Toncovich, Adrián Andrés. Universidad Nacional del Sur. Departamento de Ingeniería; ArgentinaFil: Rossit, Daniel Alejandro. 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: Rossit, Diego Gabriel. 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; ArgentinaGrowing Science2019-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/112474Toncovich, Adrián Andrés; Rossit, Daniel Alejandro; Frutos, Mariano; Rossit, Diego Gabriel; Solving a multi-objective manufacturing cell scheduling problem with the consideration of warehouses using a simulated annealing based procedure; Growing Science; International Journal of Industrial Engineering Computations; 10; 1; 1-2019; 1-161923-29261923-2934CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://growingscience.com/beta/ijiec/2830-solving-a-multi-objective-manufacturing-cell-scheduling-problem-with-the-consideration-of-warehouses-using-a-simulated-annealing-based-procedure.htmlinfo:eu-repo/semantics/altIdentifier/doi/10.5267/j.ijiec.2018.6.001info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:47:15Zoai:ri.conicet.gov.ar:11336/112474instacron: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:34982025-09-29 09:47:15.678CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Solving a multi-objective manufacturing cell scheduling problem with the consideration of warehouses using a simulated annealing based procedure
title Solving a multi-objective manufacturing cell scheduling problem with the consideration of warehouses using a simulated annealing based procedure
spellingShingle Solving a multi-objective manufacturing cell scheduling problem with the consideration of warehouses using a simulated annealing based procedure
Toncovich, Adrián Andrés
ANNEALING
FLOW-SHOP
MULTI-OBJECTIVE OPTIMIZATION
PARETO ARCHIVED SIMULATED
PRODUCTION SCHEDULING
WAREHOUSES
title_short Solving a multi-objective manufacturing cell scheduling problem with the consideration of warehouses using a simulated annealing based procedure
title_full Solving a multi-objective manufacturing cell scheduling problem with the consideration of warehouses using a simulated annealing based procedure
title_fullStr Solving a multi-objective manufacturing cell scheduling problem with the consideration of warehouses using a simulated annealing based procedure
title_full_unstemmed Solving a multi-objective manufacturing cell scheduling problem with the consideration of warehouses using a simulated annealing based procedure
title_sort Solving a multi-objective manufacturing cell scheduling problem with the consideration of warehouses using a simulated annealing based procedure
dc.creator.none.fl_str_mv Toncovich, Adrián Andrés
Rossit, Daniel Alejandro
Frutos, Mariano
Rossit, Diego Gabriel
author Toncovich, Adrián Andrés
author_facet Toncovich, Adrián Andrés
Rossit, Daniel Alejandro
Frutos, Mariano
Rossit, Diego Gabriel
author_role author
author2 Rossit, Daniel Alejandro
Frutos, Mariano
Rossit, Diego Gabriel
author2_role author
author
author
dc.subject.none.fl_str_mv ANNEALING
FLOW-SHOP
MULTI-OBJECTIVE OPTIMIZATION
PARETO ARCHIVED SIMULATED
PRODUCTION SCHEDULING
WAREHOUSES
topic ANNEALING
FLOW-SHOP
MULTI-OBJECTIVE OPTIMIZATION
PARETO ARCHIVED SIMULATED
PRODUCTION SCHEDULING
WAREHOUSES
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 competition manufacturing companies face has driven the development of novel and efficient methods that enhance the decision making process. In this work, a specific flow shop scheduling problem of practical interest in the industry is presented and formalized using a mathematical programming model. The problem considers a manufacturing system arranged as a work cell that takes into account the transport operations of raw material and final products between the manufacturing cell and warehouses. For solving this problem, we present a multiobjective metaheuristic strategy based on simulated annealing, the Pareto Archived Simulated Annealing (PASA). We tested this strategy on two kinds of benchmark problem sets proposed by the authors. The first group is composed by small-sized problems. On these tests, PASA was able to obtain optimal or near-optimal solutions in significantly short computing times. In order to complete the analysis, we compared these results to the exact Pareto front of the instances obtained with augmented ε-constraint method. Then, we also tested the algorithm in a set of larger problems to evaluate its performance in more extensive search spaces. We performed this assessment through an analysis of the hypervolume metric. Both sets of tests showed the competitiveness of the Pareto Archived Simulated Annealing to efficiently solve this problem and obtain good quality solutions while using reasonable computational resources.
Fil: Toncovich, Adrián Andrés. Universidad Nacional del Sur. Departamento de Ingeniería; Argentina
Fil: Rossit, Daniel Alejandro. 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: Rossit, Diego Gabriel. 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
description The competition manufacturing companies face has driven the development of novel and efficient methods that enhance the decision making process. In this work, a specific flow shop scheduling problem of practical interest in the industry is presented and formalized using a mathematical programming model. The problem considers a manufacturing system arranged as a work cell that takes into account the transport operations of raw material and final products between the manufacturing cell and warehouses. For solving this problem, we present a multiobjective metaheuristic strategy based on simulated annealing, the Pareto Archived Simulated Annealing (PASA). We tested this strategy on two kinds of benchmark problem sets proposed by the authors. The first group is composed by small-sized problems. On these tests, PASA was able to obtain optimal or near-optimal solutions in significantly short computing times. In order to complete the analysis, we compared these results to the exact Pareto front of the instances obtained with augmented ε-constraint method. Then, we also tested the algorithm in a set of larger problems to evaluate its performance in more extensive search spaces. We performed this assessment through an analysis of the hypervolume metric. Both sets of tests showed the competitiveness of the Pareto Archived Simulated Annealing to efficiently solve this problem and obtain good quality solutions while using reasonable computational resources.
publishDate 2019
dc.date.none.fl_str_mv 2019-01
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/11336/112474
Toncovich, Adrián Andrés; Rossit, Daniel Alejandro; Frutos, Mariano; Rossit, Diego Gabriel; Solving a multi-objective manufacturing cell scheduling problem with the consideration of warehouses using a simulated annealing based procedure; Growing Science; International Journal of Industrial Engineering Computations; 10; 1; 1-2019; 1-16
1923-2926
1923-2934
CONICET Digital
CONICET
url http://hdl.handle.net/11336/112474
identifier_str_mv Toncovich, Adrián Andrés; Rossit, Daniel Alejandro; Frutos, Mariano; Rossit, Diego Gabriel; Solving a multi-objective manufacturing cell scheduling problem with the consideration of warehouses using a simulated annealing based procedure; Growing Science; International Journal of Industrial Engineering Computations; 10; 1; 1-2019; 1-16
1923-2926
1923-2934
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://growingscience.com/beta/ijiec/2830-solving-a-multi-objective-manufacturing-cell-scheduling-problem-with-the-consideration-of-warehouses-using-a-simulated-annealing-based-procedure.html
info:eu-repo/semantics/altIdentifier/doi/10.5267/j.ijiec.2018.6.001
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Growing Science
publisher.none.fl_str_mv Growing Science
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 13.070432

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