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Customer demand-driven low-carbon vehicles combined strategy and route optimisation integrated decision

With the optimal operating cost and optimal carbon emission target of the chemical logistics companies, a low-carbon routing optimisation with a multi-energy type vehicle combined problem is proposed by considering the concept of the logistics companies’ low-carbon behaviour. An integrated decision-...

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Autores principales: Liu, Hanwen, Liu, Xiaobing, Islam, Sardar M. N., Yu, Xueqiao, Miao, Qiqi, Chen, Yapin, Lin, Lin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8445927/
https://www.ncbi.nlm.nih.gov/pubmed/34531499
http://dx.doi.org/10.1038/s41598-021-98028-2
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author Liu, Hanwen
Liu, Xiaobing
Islam, Sardar M. N.
Yu, Xueqiao
Miao, Qiqi
Chen, Yapin
Lin, Lin
author_facet Liu, Hanwen
Liu, Xiaobing
Islam, Sardar M. N.
Yu, Xueqiao
Miao, Qiqi
Chen, Yapin
Lin, Lin
author_sort Liu, Hanwen
collection PubMed
description With the optimal operating cost and optimal carbon emission target of the chemical logistics companies, a low-carbon routing optimisation with a multi-energy type vehicle combined problem is proposed by considering the concept of the logistics companies’ low-carbon behaviour. An integrated decision-making of multi-energy type vehicles combined strategy and route optimisation based on customer demand is presented, and an improved genetic algorithm is designed. A case study is then applied based on the data collected from the case research. The effectiveness of the improved genetic algorithm is tested. The two joint objectives of operating cost and carbon emission are examined through the cost analysis of environmental energy vehicles and traditional energy vehicles in different combination scenarios. The case analysis shows that a rational multi-energy type vehicle combination with route optimisation has a significant correlation with the operating cost and carbon emissions, while the environmental vehicle purchasing cost reduction and subsidy policy affect the operating cost.
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spelling pubmed-84459272021-09-20 Customer demand-driven low-carbon vehicles combined strategy and route optimisation integrated decision Liu, Hanwen Liu, Xiaobing Islam, Sardar M. N. Yu, Xueqiao Miao, Qiqi Chen, Yapin Lin, Lin Sci Rep Article With the optimal operating cost and optimal carbon emission target of the chemical logistics companies, a low-carbon routing optimisation with a multi-energy type vehicle combined problem is proposed by considering the concept of the logistics companies’ low-carbon behaviour. An integrated decision-making of multi-energy type vehicles combined strategy and route optimisation based on customer demand is presented, and an improved genetic algorithm is designed. A case study is then applied based on the data collected from the case research. The effectiveness of the improved genetic algorithm is tested. The two joint objectives of operating cost and carbon emission are examined through the cost analysis of environmental energy vehicles and traditional energy vehicles in different combination scenarios. The case analysis shows that a rational multi-energy type vehicle combination with route optimisation has a significant correlation with the operating cost and carbon emissions, while the environmental vehicle purchasing cost reduction and subsidy policy affect the operating cost. Nature Publishing Group UK 2021-09-16 /pmc/articles/PMC8445927/ /pubmed/34531499 http://dx.doi.org/10.1038/s41598-021-98028-2 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Liu, Hanwen
Liu, Xiaobing
Islam, Sardar M. N.
Yu, Xueqiao
Miao, Qiqi
Chen, Yapin
Lin, Lin
Customer demand-driven low-carbon vehicles combined strategy and route optimisation integrated decision
title Customer demand-driven low-carbon vehicles combined strategy and route optimisation integrated decision
title_full Customer demand-driven low-carbon vehicles combined strategy and route optimisation integrated decision
title_fullStr Customer demand-driven low-carbon vehicles combined strategy and route optimisation integrated decision
title_full_unstemmed Customer demand-driven low-carbon vehicles combined strategy and route optimisation integrated decision
title_short Customer demand-driven low-carbon vehicles combined strategy and route optimisation integrated decision
title_sort customer demand-driven low-carbon vehicles combined strategy and route optimisation integrated decision
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8445927/
https://www.ncbi.nlm.nih.gov/pubmed/34531499
http://dx.doi.org/10.1038/s41598-021-98028-2
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