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A Mixed Decision Strategy for Freight and Passenger Transportation in Metro Systems

This paper proposes a mixed decision strategy for freight and passenger transportation in metro systems during off-peak hours (MTS-OPH). The definition of the mixed decision strategy is proposed, and fixed and flexible loading modes are considered for different passenger flow volumes. A mathematical...

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Detalles Bibliográficos
Autores principales: Ye, Yutao, Guo, Junhua, Yan, Lixin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8654573/
https://www.ncbi.nlm.nih.gov/pubmed/34899895
http://dx.doi.org/10.1155/2021/5412016
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author Ye, Yutao
Guo, Junhua
Yan, Lixin
author_facet Ye, Yutao
Guo, Junhua
Yan, Lixin
author_sort Ye, Yutao
collection PubMed
description This paper proposes a mixed decision strategy for freight and passenger transportation in metro systems during off-peak hours (MTS-OPH). The definition of the mixed decision strategy is proposed, and fixed and flexible loading modes are considered for different passenger flow volumes. A mathematical model of the MTS-OPH is proposed and solved using an improved variable neighborhood search algorithm. Case studies demonstrate the performance and applicability of the proposed model and algorithm, and the MTS-OPH is discussed for different delivery distances, passenger flows, and metro network types. The proposed strategy is suitable for long-distance delivery, and the proposed model framework can be applied to different types of metro networks with different levels of complexity. The mixed decision strategy provides a decision support tool for metro and freight companies and can propose corresponding solutions according to different passenger flows.
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spelling pubmed-86545732021-12-09 A Mixed Decision Strategy for Freight and Passenger Transportation in Metro Systems Ye, Yutao Guo, Junhua Yan, Lixin Comput Intell Neurosci Research Article This paper proposes a mixed decision strategy for freight and passenger transportation in metro systems during off-peak hours (MTS-OPH). The definition of the mixed decision strategy is proposed, and fixed and flexible loading modes are considered for different passenger flow volumes. A mathematical model of the MTS-OPH is proposed and solved using an improved variable neighborhood search algorithm. Case studies demonstrate the performance and applicability of the proposed model and algorithm, and the MTS-OPH is discussed for different delivery distances, passenger flows, and metro network types. The proposed strategy is suitable for long-distance delivery, and the proposed model framework can be applied to different types of metro networks with different levels of complexity. The mixed decision strategy provides a decision support tool for metro and freight companies and can propose corresponding solutions according to different passenger flows. Hindawi 2021-12-01 /pmc/articles/PMC8654573/ /pubmed/34899895 http://dx.doi.org/10.1155/2021/5412016 Text en Copyright © 2021 Yutao Ye et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Ye, Yutao
Guo, Junhua
Yan, Lixin
A Mixed Decision Strategy for Freight and Passenger Transportation in Metro Systems
title A Mixed Decision Strategy for Freight and Passenger Transportation in Metro Systems
title_full A Mixed Decision Strategy for Freight and Passenger Transportation in Metro Systems
title_fullStr A Mixed Decision Strategy for Freight and Passenger Transportation in Metro Systems
title_full_unstemmed A Mixed Decision Strategy for Freight and Passenger Transportation in Metro Systems
title_short A Mixed Decision Strategy for Freight and Passenger Transportation in Metro Systems
title_sort mixed decision strategy for freight and passenger transportation in metro systems
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8654573/
https://www.ncbi.nlm.nih.gov/pubmed/34899895
http://dx.doi.org/10.1155/2021/5412016
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