Comparison of MOEAs in an Optimization-Decision Methodology for a Joint Order Batching and Picking System

Autores
Miguel, Fabio Maximiliano; Frutos, Mariano; Méndez, Máximo; Tohmé, Fernando Abel; González, Begoña
Año de publicación
2024
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
This paper investigates the performance of a two-stage multi-criteria decision-making procedure for order scheduling problems. These problems are represented by a novel nonlinear mixed integer program. Hybridizations of three Multi-Objective Evolutionary Algorithms (MOEAs) based on dominance relations are studied and compared to solve small, medium, and large instances of the joint order batching and picking problem in storage systems with multiple blocks of two and three dimensions. The performance of these methods is compared using a set of well-known metrics and running an extensive battery of simulations based on a methodology widely used in the literature. The main contributions of this paper are (1) the hybridization of MOEAs to deal efficiently with the combination of orders in one or several picking tours, scheduling them for each picker, and (2) a multi-criteria approach to scheduling multiple picking teams for each wave of orders. Based on the experimental results obtained, it can be stated that, in environments with a large number of different items and orders with high variability in volume, the proposed approach can significantly reduce operating costs while allowing the decision-maker to anticipate the positioning of orders in the dispatch area.
Fil: Miguel, Fabio Maximiliano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Confluencia; Argentina. Universidad Nacional de Río Negro; 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
Fil: Méndez, Máximo. Universidad de Las Palmas de Gran Canaria; España. Instituto Universitario de Sistemas Inteligentes Siani; España
Fil: Tohmé, Fernando Abel. 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
Fil: González, Begoña. Universidad de Las Palmas de Gran Canaria; España. Instituto Universitario de Sistemas Inteligentes Siani; España
Materia
MULTIPLE CRITERIA DECISION-MAKING
MULTI-OBJECTIVE EVOLUTIONARY ALGORITHMS
ORDER BATCHING PROBLEM
ORDER PICKING PROBLEM
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:11336/234492
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/234492
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Comparison of MOEAs in an Optimization-Decision Methodology for a Joint Order Batching and Picking SystemMiguel, Fabio MaximilianoFrutos, MarianoMéndez, MáximoTohmé, Fernando AbelGonzález, BegoñaMULTIPLE CRITERIA DECISION-MAKINGMULTI-OBJECTIVE EVOLUTIONARY ALGORITHMSORDER BATCHING PROBLEMORDER PICKING PROBLEMhttps://purl.org/becyt/ford/5.2https://purl.org/becyt/ford/5This paper investigates the performance of a two-stage multi-criteria decision-making procedure for order scheduling problems. These problems are represented by a novel nonlinear mixed integer program. Hybridizations of three Multi-Objective Evolutionary Algorithms (MOEAs) based on dominance relations are studied and compared to solve small, medium, and large instances of the joint order batching and picking problem in storage systems with multiple blocks of two and three dimensions. The performance of these methods is compared using a set of well-known metrics and running an extensive battery of simulations based on a methodology widely used in the literature. The main contributions of this paper are (1) the hybridization of MOEAs to deal efficiently with the combination of orders in one or several picking tours, scheduling them for each picker, and (2) a multi-criteria approach to scheduling multiple picking teams for each wave of orders. Based on the experimental results obtained, it can be stated that, in environments with a large number of different items and orders with high variability in volume, the proposed approach can significantly reduce operating costs while allowing the decision-maker to anticipate the positioning of orders in the dispatch area.Fil: Miguel, Fabio Maximiliano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Confluencia; Argentina. Universidad Nacional de Río Negro; 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; ArgentinaFil: Méndez, Máximo. Universidad de Las Palmas de Gran Canaria; España. Instituto Universitario de Sistemas Inteligentes Siani; EspañaFil: Tohmé, Fernando Abel. 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; ArgentinaFil: González, Begoña. Universidad de Las Palmas de Gran Canaria; España. Instituto Universitario de Sistemas Inteligentes Siani; EspañaMultidisciplinary Digital Publishing Institute2024-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/234492Miguel, Fabio Maximiliano; Frutos, Mariano; Méndez, Máximo; Tohmé, Fernando Abel; González, Begoña; Comparison of MOEAs in an Optimization-Decision Methodology for a Joint Order Batching and Picking System; Multidisciplinary Digital Publishing Institute; Mathematics; 12; 8; 4-2024; 1-232227-7390CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.mdpi.com/2227-7390/12/8/1246info:eu-repo/semantics/altIdentifier/doi/10.3390/math12081246info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:41:47Zoai:ri.conicet.gov.ar:11336/234492instacron: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 10:41:48.208CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Comparison of MOEAs in an Optimization-Decision Methodology for a Joint Order Batching and Picking System
title Comparison of MOEAs in an Optimization-Decision Methodology for a Joint Order Batching and Picking System
spellingShingle Comparison of MOEAs in an Optimization-Decision Methodology for a Joint Order Batching and Picking System
Miguel, Fabio Maximiliano
MULTIPLE CRITERIA DECISION-MAKING
MULTI-OBJECTIVE EVOLUTIONARY ALGORITHMS
ORDER BATCHING PROBLEM
ORDER PICKING PROBLEM
title_short Comparison of MOEAs in an Optimization-Decision Methodology for a Joint Order Batching and Picking System
title_full Comparison of MOEAs in an Optimization-Decision Methodology for a Joint Order Batching and Picking System
title_fullStr Comparison of MOEAs in an Optimization-Decision Methodology for a Joint Order Batching and Picking System
title_full_unstemmed Comparison of MOEAs in an Optimization-Decision Methodology for a Joint Order Batching and Picking System
title_sort Comparison of MOEAs in an Optimization-Decision Methodology for a Joint Order Batching and Picking System
dc.creator.none.fl_str_mv Miguel, Fabio Maximiliano
Frutos, Mariano
Méndez, Máximo
Tohmé, Fernando Abel
González, Begoña
author Miguel, Fabio Maximiliano
author_facet Miguel, Fabio Maximiliano
Frutos, Mariano
Méndez, Máximo
Tohmé, Fernando Abel
González, Begoña
author_role author
author2 Frutos, Mariano
Méndez, Máximo
Tohmé, Fernando Abel
González, Begoña
author2_role author
author
author
author
dc.subject.none.fl_str_mv MULTIPLE CRITERIA DECISION-MAKING
MULTI-OBJECTIVE EVOLUTIONARY ALGORITHMS
ORDER BATCHING PROBLEM
ORDER PICKING PROBLEM
topic MULTIPLE CRITERIA DECISION-MAKING
MULTI-OBJECTIVE EVOLUTIONARY ALGORITHMS
ORDER BATCHING PROBLEM
ORDER PICKING PROBLEM
purl_subject.fl_str_mv https://purl.org/becyt/ford/5.2
https://purl.org/becyt/ford/5
dc.description.none.fl_txt_mv This paper investigates the performance of a two-stage multi-criteria decision-making procedure for order scheduling problems. These problems are represented by a novel nonlinear mixed integer program. Hybridizations of three Multi-Objective Evolutionary Algorithms (MOEAs) based on dominance relations are studied and compared to solve small, medium, and large instances of the joint order batching and picking problem in storage systems with multiple blocks of two and three dimensions. The performance of these methods is compared using a set of well-known metrics and running an extensive battery of simulations based on a methodology widely used in the literature. The main contributions of this paper are (1) the hybridization of MOEAs to deal efficiently with the combination of orders in one or several picking tours, scheduling them for each picker, and (2) a multi-criteria approach to scheduling multiple picking teams for each wave of orders. Based on the experimental results obtained, it can be stated that, in environments with a large number of different items and orders with high variability in volume, the proposed approach can significantly reduce operating costs while allowing the decision-maker to anticipate the positioning of orders in the dispatch area.
Fil: Miguel, Fabio Maximiliano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Confluencia; Argentina. Universidad Nacional de Río Negro; 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
Fil: Méndez, Máximo. Universidad de Las Palmas de Gran Canaria; España. Instituto Universitario de Sistemas Inteligentes Siani; España
Fil: Tohmé, Fernando Abel. 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
Fil: González, Begoña. Universidad de Las Palmas de Gran Canaria; España. Instituto Universitario de Sistemas Inteligentes Siani; España
description This paper investigates the performance of a two-stage multi-criteria decision-making procedure for order scheduling problems. These problems are represented by a novel nonlinear mixed integer program. Hybridizations of three Multi-Objective Evolutionary Algorithms (MOEAs) based on dominance relations are studied and compared to solve small, medium, and large instances of the joint order batching and picking problem in storage systems with multiple blocks of two and three dimensions. The performance of these methods is compared using a set of well-known metrics and running an extensive battery of simulations based on a methodology widely used in the literature. The main contributions of this paper are (1) the hybridization of MOEAs to deal efficiently with the combination of orders in one or several picking tours, scheduling them for each picker, and (2) a multi-criteria approach to scheduling multiple picking teams for each wave of orders. Based on the experimental results obtained, it can be stated that, in environments with a large number of different items and orders with high variability in volume, the proposed approach can significantly reduce operating costs while allowing the decision-maker to anticipate the positioning of orders in the dispatch area.
publishDate 2024
dc.date.none.fl_str_mv 2024-04
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/11336/234492
Miguel, Fabio Maximiliano; Frutos, Mariano; Méndez, Máximo; Tohmé, Fernando Abel; González, Begoña; Comparison of MOEAs in an Optimization-Decision Methodology for a Joint Order Batching and Picking System; Multidisciplinary Digital Publishing Institute; Mathematics; 12; 8; 4-2024; 1-23
2227-7390
CONICET Digital
CONICET
url http://hdl.handle.net/11336/234492
identifier_str_mv Miguel, Fabio Maximiliano; Frutos, Mariano; Méndez, Máximo; Tohmé, Fernando Abel; González, Begoña; Comparison of MOEAs in an Optimization-Decision Methodology for a Joint Order Batching and Picking System; Multidisciplinary Digital Publishing Institute; Mathematics; 12; 8; 4-2024; 1-23
2227-7390
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.mdpi.com/2227-7390/12/8/1246
info:eu-repo/semantics/altIdentifier/doi/10.3390/math12081246
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
dc.publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute
publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute
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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