Improved artificial bee colony algorithm for vehicle routing problem with time windows

This paper investigates a well-known complex combinatorial problem known as the vehicle routing problem with time windows (VRPTW). Unlike the standard vehicle routing problem, each customer in the VRPTW is served within a given time constraint. This paper solves the VRPTW using an improved artificia...

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Detalles Bibliográficos
Autores principales: Yao, Baozhen, Yan, Qianqian, Zhang, Mengjie, Yang, Yunong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5621664/
https://www.ncbi.nlm.nih.gov/pubmed/28961252
http://dx.doi.org/10.1371/journal.pone.0181275
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author Yao, Baozhen
Yan, Qianqian
Zhang, Mengjie
Yang, Yunong
author_facet Yao, Baozhen
Yan, Qianqian
Zhang, Mengjie
Yang, Yunong
author_sort Yao, Baozhen
collection PubMed
description This paper investigates a well-known complex combinatorial problem known as the vehicle routing problem with time windows (VRPTW). Unlike the standard vehicle routing problem, each customer in the VRPTW is served within a given time constraint. This paper solves the VRPTW using an improved artificial bee colony (IABC) algorithm. The performance of this algorithm is improved by a local optimization based on a crossover operation and a scanning strategy. Finally, the effectiveness of the IABC is evaluated on some well-known benchmarks. The results demonstrate the power of IABC algorithm in solving the VRPTW.
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spelling pubmed-56216642017-10-17 Improved artificial bee colony algorithm for vehicle routing problem with time windows Yao, Baozhen Yan, Qianqian Zhang, Mengjie Yang, Yunong PLoS One Research Article This paper investigates a well-known complex combinatorial problem known as the vehicle routing problem with time windows (VRPTW). Unlike the standard vehicle routing problem, each customer in the VRPTW is served within a given time constraint. This paper solves the VRPTW using an improved artificial bee colony (IABC) algorithm. The performance of this algorithm is improved by a local optimization based on a crossover operation and a scanning strategy. Finally, the effectiveness of the IABC is evaluated on some well-known benchmarks. The results demonstrate the power of IABC algorithm in solving the VRPTW. Public Library of Science 2017-09-29 /pmc/articles/PMC5621664/ /pubmed/28961252 http://dx.doi.org/10.1371/journal.pone.0181275 Text en © 2017 Yao 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
Yao, Baozhen
Yan, Qianqian
Zhang, Mengjie
Yang, Yunong
Improved artificial bee colony algorithm for vehicle routing problem with time windows
title Improved artificial bee colony algorithm for vehicle routing problem with time windows
title_full Improved artificial bee colony algorithm for vehicle routing problem with time windows
title_fullStr Improved artificial bee colony algorithm for vehicle routing problem with time windows
title_full_unstemmed Improved artificial bee colony algorithm for vehicle routing problem with time windows
title_short Improved artificial bee colony algorithm for vehicle routing problem with time windows
title_sort improved artificial bee colony algorithm for vehicle routing problem with time windows
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5621664/
https://www.ncbi.nlm.nih.gov/pubmed/28961252
http://dx.doi.org/10.1371/journal.pone.0181275
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AT yanqianqian improvedartificialbeecolonyalgorithmforvehicleroutingproblemwithtimewindows
AT zhangmengjie improvedartificialbeecolonyalgorithmforvehicleroutingproblemwithtimewindows
AT yangyunong improvedartificialbeecolonyalgorithmforvehicleroutingproblemwithtimewindows

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