A memetic algorithm for the integral OBP/OPP problem in a logistics distribution center

Autores
Miguel, Fabio; Frutos, Mariano; Tohmé, Fernando Abel; Rossit, Daniel Alejandro
Año de publicación
2019
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
In this paper, we present a new decision-making tool aimed at improving the efficiency of the operational planning of pick-up processes in logistic distribution centers. It is based on a memetic algorithm (MA) solving both the Order Batching Problem (OBP) and the Order Picking Problem (OPP). The result yields a sequence of simultaneous pick up operations of lots for different clients in a storing facility, satisfying a previously defined distribution plan. The objective is the minimization of the operational cost of the entire process, which is directly proportional to the time spent on different activities involved. The failure to satisfy the conditions, either leads to overstocking, delays in delivery or creates inefficiency costs. The analysis of the results obtained with our algorithmic tool indicates that it has a good performance in comparison with other known algorithms used to solve this kind of problem.
Fil: Miguel, Fabio. 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: 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: 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
Materia
OGISTICS
OPTIMIZATION
ORDER BATCHING PROBLEM
ORDER PICKING PROBLEM
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:11336/92794
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/92794
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling A memetic algorithm for the integral OBP/OPP problem in a logistics distribution centerMiguel, FabioFrutos, MarianoTohmé, Fernando AbelRossit, Daniel AlejandroOGISTICSOPTIMIZATIONORDER BATCHING PROBLEMORDER PICKING PROBLEMhttps://purl.org/becyt/ford/2.11https://purl.org/becyt/ford/2In this paper, we present a new decision-making tool aimed at improving the efficiency of the operational planning of pick-up processes in logistic distribution centers. It is based on a memetic algorithm (MA) solving both the Order Batching Problem (OBP) and the Order Picking Problem (OPP). The result yields a sequence of simultaneous pick up operations of lots for different clients in a storing facility, satisfying a previously defined distribution plan. The objective is the minimization of the operational cost of the entire process, which is directly proportional to the time spent on different activities involved. The failure to satisfy the conditions, either leads to overstocking, delays in delivery or creates inefficiency costs. The analysis of the results obtained with our algorithmic tool indicates that it has a good performance in comparison with other known algorithms used to solve this kind of problem.Fil: Miguel, Fabio. 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: 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: 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; 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/11336/92794Miguel, Fabio; Frutos, Mariano; Tohmé, Fernando Abel; Rossit, Daniel Alejandro; A memetic algorithm for the integral OBP/OPP problem in a logistics distribution center; Growing Science; Uncertain Supply Chain Management; 7; 2; 1-2019; 203-2142291-68222291-6830CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://growingscience.com/beta/uscm/2970-a-memetic-algorithm-for-the-integral-obp-opp-problem-in-a-logistics-distribution-center.htmlinfo:eu-repo/semantics/altIdentifier/url/http://www.growingscience.com/uscm/Vol7/uscm_2018_23.pdfinfo:eu-repo/semantics/altIdentifier/doi/10.5267/j.uscm.2018.10.005info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:40:52Zoai:ri.conicet.gov.ar:11336/92794instacron: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 09:40:52.884CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A memetic algorithm for the integral OBP/OPP problem in a logistics distribution center
title A memetic algorithm for the integral OBP/OPP problem in a logistics distribution center
spellingShingle A memetic algorithm for the integral OBP/OPP problem in a logistics distribution center
Miguel, Fabio
OGISTICS
OPTIMIZATION
ORDER BATCHING PROBLEM
ORDER PICKING PROBLEM
title_short A memetic algorithm for the integral OBP/OPP problem in a logistics distribution center
title_full A memetic algorithm for the integral OBP/OPP problem in a logistics distribution center
title_fullStr A memetic algorithm for the integral OBP/OPP problem in a logistics distribution center
title_full_unstemmed A memetic algorithm for the integral OBP/OPP problem in a logistics distribution center
title_sort A memetic algorithm for the integral OBP/OPP problem in a logistics distribution center
dc.creator.none.fl_str_mv Miguel, Fabio
Frutos, Mariano
Tohmé, Fernando Abel
Rossit, Daniel Alejandro
author Miguel, Fabio
author_facet Miguel, Fabio
Frutos, Mariano
Tohmé, Fernando Abel
Rossit, Daniel Alejandro
author_role author
author2 Frutos, Mariano
Tohmé, Fernando Abel
Rossit, Daniel Alejandro
author2_role author
author
author
dc.subject.none.fl_str_mv OGISTICS
OPTIMIZATION
ORDER BATCHING PROBLEM
ORDER PICKING PROBLEM
topic OGISTICS
OPTIMIZATION
ORDER BATCHING PROBLEM
ORDER PICKING PROBLEM
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.11
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv In this paper, we present a new decision-making tool aimed at improving the efficiency of the operational planning of pick-up processes in logistic distribution centers. It is based on a memetic algorithm (MA) solving both the Order Batching Problem (OBP) and the Order Picking Problem (OPP). The result yields a sequence of simultaneous pick up operations of lots for different clients in a storing facility, satisfying a previously defined distribution plan. The objective is the minimization of the operational cost of the entire process, which is directly proportional to the time spent on different activities involved. The failure to satisfy the conditions, either leads to overstocking, delays in delivery or creates inefficiency costs. The analysis of the results obtained with our algorithmic tool indicates that it has a good performance in comparison with other known algorithms used to solve this kind of problem.
Fil: Miguel, Fabio. 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: 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: 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
description In this paper, we present a new decision-making tool aimed at improving the efficiency of the operational planning of pick-up processes in logistic distribution centers. It is based on a memetic algorithm (MA) solving both the Order Batching Problem (OBP) and the Order Picking Problem (OPP). The result yields a sequence of simultaneous pick up operations of lots for different clients in a storing facility, satisfying a previously defined distribution plan. The objective is the minimization of the operational cost of the entire process, which is directly proportional to the time spent on different activities involved. The failure to satisfy the conditions, either leads to overstocking, delays in delivery or creates inefficiency costs. The analysis of the results obtained with our algorithmic tool indicates that it has a good performance in comparison with other known algorithms used to solve this kind of problem.
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/11336/92794
Miguel, Fabio; Frutos, Mariano; Tohmé, Fernando Abel; Rossit, Daniel Alejandro; A memetic algorithm for the integral OBP/OPP problem in a logistics distribution center; Growing Science; Uncertain Supply Chain Management; 7; 2; 1-2019; 203-214
2291-6822
2291-6830
CONICET Digital
CONICET
url http://hdl.handle.net/11336/92794
identifier_str_mv Miguel, Fabio; Frutos, Mariano; Tohmé, Fernando Abel; Rossit, Daniel Alejandro; A memetic algorithm for the integral OBP/OPP problem in a logistics distribution center; Growing Science; Uncertain Supply Chain Management; 7; 2; 1-2019; 203-214
2291-6822
2291-6830
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/uscm/2970-a-memetic-algorithm-for-the-integral-obp-opp-problem-in-a-logistics-distribution-center.html
info:eu-repo/semantics/altIdentifier/url/http://www.growingscience.com/uscm/Vol7/uscm_2018_23.pdf
info:eu-repo/semantics/altIdentifier/doi/10.5267/j.uscm.2018.10.005
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
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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