A discrete particle swarm optimization to solve the put-away routing problem in distribution centres

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/)

Detalles Bibliográficos
Autores: Gómez Montoya, Rodrigo Andrés, Cano, José Alejandro, Cortés, Pablo, Salazar Arrieta, Fernando
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2020
País:España
Institución:Universidad de Sevilla (US)
Repositorio:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/146644
Acceso en línea:https://hdl.handle.net/11441/146644
https://doi.org/10.3390/computation8040099
Access Level:acceso abierto
Palabra clave:Put-away routing
Distribution centre
Discrete particle swarm optimization
Order picking
Warehouse management
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spelling A discrete particle swarm optimization to solve the put-away routing problem in distribution centresGómez Montoya, Rodrigo AndrésCano, José AlejandroCortés, PabloSalazar Arrieta, FernandoPut-away routingDistribution centreDiscrete particle swarm optimizationOrder pickingWarehouse managementThis article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/)Put-away operations typically consist of moving products from depots to allocated storage locations using either operators or Material Handling Equipment (MHE), accounting for important operative costs in warehouses and impacting operations efficiency. Therefore, this paper aims to formulate and solve a Put-away Routing Problem (PRP) in distribution centres (DCs). This PRP formulation represents a novel approach due to the consideration of a fleet of homogeneous Material Handling Equipment (MHE), heterogeneous products linked to a put-away list size, depot location and multi-parallel aisles in a distribution centre. It should be noted that the slotting problem, rather than the PRP, has usually been studied in the literature, whereas the PRP is addressed in this paper. The PRP is solved using a discrete particle swarm optimization (PSO) algorithm that is compared to tabu search approaches (Classical Tabu Search (CTS), Tabu Search (TS) 2-Opt) and an empirical rule. As a result, it was found that a discrete PSO generates the best solutions, as the time savings range from 2 to 13% relative to CTS and TS 2-Opt for different combinations of factor levels evaluated in the experimentation.MDPIOrganización Industrial y Gestión de Empresas II2020info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttps://hdl.handle.net/11441/146644https://doi.org/10.3390/computation8040099reponame:idUS. Depósito de Investigación de la Universidad de Sevillainstname:Universidad de Sevilla (US)InglésComputation, 8 (4), 99.https://www.mdpi.com/2079-3197/8/4/99info:eu-repo/semantics/openAccessoai:idus.us.es:11441/1466442026-06-17T12:51:07Z
dc.title.none.fl_str_mv A discrete particle swarm optimization to solve the put-away routing problem in distribution centres
title A discrete particle swarm optimization to solve the put-away routing problem in distribution centres
spellingShingle A discrete particle swarm optimization to solve the put-away routing problem in distribution centres
Gómez Montoya, Rodrigo Andrés
Put-away routing
Distribution centre
Discrete particle swarm optimization
Order picking
Warehouse management
title_short A discrete particle swarm optimization to solve the put-away routing problem in distribution centres
title_full A discrete particle swarm optimization to solve the put-away routing problem in distribution centres
title_fullStr A discrete particle swarm optimization to solve the put-away routing problem in distribution centres
title_full_unstemmed A discrete particle swarm optimization to solve the put-away routing problem in distribution centres
title_sort A discrete particle swarm optimization to solve the put-away routing problem in distribution centres
dc.creator.none.fl_str_mv Gómez Montoya, Rodrigo Andrés
Cano, José Alejandro
Cortés, Pablo
Salazar Arrieta, Fernando
author Gómez Montoya, Rodrigo Andrés
author_facet Gómez Montoya, Rodrigo Andrés
Cano, José Alejandro
Cortés, Pablo
Salazar Arrieta, Fernando
author_role author
author2 Cano, José Alejandro
Cortés, Pablo
Salazar Arrieta, Fernando
author2_role author
author
author
dc.contributor.none.fl_str_mv Organización Industrial y Gestión de Empresas II
dc.subject.none.fl_str_mv Put-away routing
Distribution centre
Discrete particle swarm optimization
Order picking
Warehouse management
topic Put-away routing
Distribution centre
Discrete particle swarm optimization
Order picking
Warehouse management
description This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/)
publishDate 2020
dc.date.none.fl_str_mv 2020
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/11441/146644
https://doi.org/10.3390/computation8040099
url https://hdl.handle.net/11441/146644
https://doi.org/10.3390/computation8040099
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Computation, 8 (4), 99.
https://www.mdpi.com/2079-3197/8/4/99
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv reponame:idUS. Depósito de Investigación de la Universidad de Sevilla
instname:Universidad de Sevilla (US)
instname_str Universidad de Sevilla (US)
reponame_str idUS. Depósito de Investigación de la Universidad de Sevilla
collection idUS. Depósito de Investigación de la Universidad de Sevilla
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,300724

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