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Hybrid genetic algorithm-based optimisation of the batch order picking in a dense mobile rack warehouse

The utilization of a storage space can be considerably improved by using dense mobile racks. However, it is necessary to perform an optimisation study on the order picking to reduce the time cost as much as possible. According to the channel location information that needs to be sorted, the multiple...

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Detalles Bibliográficos
Autores principales: Yang, Jianglong, Zhou, Li, Liu, Huwei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8021203/
https://www.ncbi.nlm.nih.gov/pubmed/33819281
http://dx.doi.org/10.1371/journal.pone.0249543
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author Yang, Jianglong
Zhou, Li
Liu, Huwei
author_facet Yang, Jianglong
Zhou, Li
Liu, Huwei
author_sort Yang, Jianglong
collection PubMed
description The utilization of a storage space can be considerably improved by using dense mobile racks. However, it is necessary to perform an optimisation study on the order picking to reduce the time cost as much as possible. According to the channel location information that needs to be sorted, the multiple orders are divided into different batches by using hierarchical clustering. On this basis, a mathematical model for the virtual order clusters formed in the batches is established to optimize the order cluster picking and rack position movement, with the minimum picking time as the objective. For this model, a hybrid genetic algorithm is designed, and the characteristics of the different examples and solution algorithms are further analysed to provide a reference for the solution of the order picking optimisation problem in a dense mobile rack warehouse.
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spelling pubmed-80212032021-04-14 Hybrid genetic algorithm-based optimisation of the batch order picking in a dense mobile rack warehouse Yang, Jianglong Zhou, Li Liu, Huwei PLoS One Research Article The utilization of a storage space can be considerably improved by using dense mobile racks. However, it is necessary to perform an optimisation study on the order picking to reduce the time cost as much as possible. According to the channel location information that needs to be sorted, the multiple orders are divided into different batches by using hierarchical clustering. On this basis, a mathematical model for the virtual order clusters formed in the batches is established to optimize the order cluster picking and rack position movement, with the minimum picking time as the objective. For this model, a hybrid genetic algorithm is designed, and the characteristics of the different examples and solution algorithms are further analysed to provide a reference for the solution of the order picking optimisation problem in a dense mobile rack warehouse. Public Library of Science 2021-04-05 /pmc/articles/PMC8021203/ /pubmed/33819281 http://dx.doi.org/10.1371/journal.pone.0249543 Text en © 2021 Yang et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Yang, Jianglong
Zhou, Li
Liu, Huwei
Hybrid genetic algorithm-based optimisation of the batch order picking in a dense mobile rack warehouse
title Hybrid genetic algorithm-based optimisation of the batch order picking in a dense mobile rack warehouse
title_full Hybrid genetic algorithm-based optimisation of the batch order picking in a dense mobile rack warehouse
title_fullStr Hybrid genetic algorithm-based optimisation of the batch order picking in a dense mobile rack warehouse
title_full_unstemmed Hybrid genetic algorithm-based optimisation of the batch order picking in a dense mobile rack warehouse
title_short Hybrid genetic algorithm-based optimisation of the batch order picking in a dense mobile rack warehouse
title_sort hybrid genetic algorithm-based optimisation of the batch order picking in a dense mobile rack warehouse
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8021203/
https://www.ncbi.nlm.nih.gov/pubmed/33819281
http://dx.doi.org/10.1371/journal.pone.0249543
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