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Customized bus passenger boarding and deboarding planning optimization model with the least number of contacts between passengers during COVID-19
The COVID-19 epidemic has had a major impact on people’s normal travel. Optimizing the control of the number of passengers boarding and deboarding the customized bus (CB) at CB stops can reduce the contact between passengers in the course of travel, which is meaningful for COVID-19 epidemic preventi...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier B.V.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8265187/ https://www.ncbi.nlm.nih.gov/pubmed/34257475 http://dx.doi.org/10.1016/j.physa.2021.126244 |
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author | Chen, Feng Peng, Haorong Ding, Wenlong Ma, Xiaoxiang Tang, Daizhong Ye, Yipeng |
author_facet | Chen, Feng Peng, Haorong Ding, Wenlong Ma, Xiaoxiang Tang, Daizhong Ye, Yipeng |
author_sort | Chen, Feng |
collection | PubMed |
description | The COVID-19 epidemic has had a major impact on people’s normal travel. Optimizing the control of the number of passengers boarding and deboarding the customized bus (CB) at CB stops can reduce the contact between passengers in the course of travel, which is meaningful for COVID-19 epidemic prevention and control. In this paper, a dynamic programming model based on nonlinear integer programming (NIP) is established to study the problem of boarding and alighting planning at various CB stops under the influence of COVID-19. Using Gurobi 9.1.1 solver, the optimal plan for passengers boarding and deboarding CB buses could be obtained. Besides, the mathematical model established in this paper can obtain the minimum value of the total number of contacts between passengers during travel under different CB numbers. It is found that the model solution results eventually form a Pareto frontier. When the number of CB buses increases, the total number of contacts between passengers will decrease This study has positive significance for ensuring the normal travel of passengers during the COVID-19 epidemic, and provides useful references for the studies about the planning of the customized bus. |
format | Online Article Text |
id | pubmed-8265187 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-82651872021-07-09 Customized bus passenger boarding and deboarding planning optimization model with the least number of contacts between passengers during COVID-19 Chen, Feng Peng, Haorong Ding, Wenlong Ma, Xiaoxiang Tang, Daizhong Ye, Yipeng Physica A Article The COVID-19 epidemic has had a major impact on people’s normal travel. Optimizing the control of the number of passengers boarding and deboarding the customized bus (CB) at CB stops can reduce the contact between passengers in the course of travel, which is meaningful for COVID-19 epidemic prevention and control. In this paper, a dynamic programming model based on nonlinear integer programming (NIP) is established to study the problem of boarding and alighting planning at various CB stops under the influence of COVID-19. Using Gurobi 9.1.1 solver, the optimal plan for passengers boarding and deboarding CB buses could be obtained. Besides, the mathematical model established in this paper can obtain the minimum value of the total number of contacts between passengers during travel under different CB numbers. It is found that the model solution results eventually form a Pareto frontier. When the number of CB buses increases, the total number of contacts between passengers will decrease This study has positive significance for ensuring the normal travel of passengers during the COVID-19 epidemic, and provides useful references for the studies about the planning of the customized bus. Elsevier B.V. 2021-11-15 2021-07-08 /pmc/articles/PMC8265187/ /pubmed/34257475 http://dx.doi.org/10.1016/j.physa.2021.126244 Text en © 2021 Elsevier B.V. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Chen, Feng Peng, Haorong Ding, Wenlong Ma, Xiaoxiang Tang, Daizhong Ye, Yipeng Customized bus passenger boarding and deboarding planning optimization model with the least number of contacts between passengers during COVID-19 |
title | Customized bus passenger boarding and deboarding planning optimization model with the least number of contacts between passengers during COVID-19 |
title_full | Customized bus passenger boarding and deboarding planning optimization model with the least number of contacts between passengers during COVID-19 |
title_fullStr | Customized bus passenger boarding and deboarding planning optimization model with the least number of contacts between passengers during COVID-19 |
title_full_unstemmed | Customized bus passenger boarding and deboarding planning optimization model with the least number of contacts between passengers during COVID-19 |
title_short | Customized bus passenger boarding and deboarding planning optimization model with the least number of contacts between passengers during COVID-19 |
title_sort | customized bus passenger boarding and deboarding planning optimization model with the least number of contacts between passengers during covid-19 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8265187/ https://www.ncbi.nlm.nih.gov/pubmed/34257475 http://dx.doi.org/10.1016/j.physa.2021.126244 |
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