Cargando…
Adapting Urban Transport Planning to the COVID-19 Pandemic: An Integrated Fermatean Fuzzy Model
The critical worldwide problem of adapting urban transport planning to COVID-19 is for the first time comprehensively addressed and solved in this study. It primarily aims to help transport planners increase the resilience of transport systems. Firstly, a multi-level decision-making hierarchy struct...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8733251/ https://www.ncbi.nlm.nih.gov/pubmed/35013703 http://dx.doi.org/10.1016/j.scs.2022.103669 |
_version_ | 1784627761526079488 |
---|---|
author | Simić, Vladimir Ivanović, Ivan Đorić, Vladimir Torkayesh, Ali Ebadi |
author_facet | Simić, Vladimir Ivanović, Ivan Đorić, Vladimir Torkayesh, Ali Ebadi |
author_sort | Simić, Vladimir |
collection | PubMed |
description | The critical worldwide problem of adapting urban transport planning to COVID-19 is for the first time comprehensively addressed and solved in this study. It primarily aims to help transport planners increase the resilience of transport systems. Firstly, a multi-level decision-making hierarchy structure based on four main criteria and 17 sub-criteria is introduced for relevant stakeholders to provide a practical framework for assessing existing transport plans. Then, a three-stage integrated Fermatean fuzzy model for adapting urban transport planning to the pandemic is presented. The model hybridizes the method based on the removal effects of criteria (MEREC) and combined compromise solution (CoCoSo) method into a unique methodological framework under the Fermatean fuzzy environment. A case study provides decision-making guidelines on how to adapt transport plans to COVID-19 in the real-world context of Belgrade, Serbia. The research findings show that the pandemic significantly changed the priorities of transport planning strategies and measures. “Non-motorized travel” is now the best alternative since its numerous short-term measures lead to better transport service. The major advantages of the introduced model are higher flexibility and a more precise fusion of experts’ preference information. The integrated Fermatean fuzzy model could be used for adapting other emerging problems to COVID-19. |
format | Online Article Text |
id | pubmed-8733251 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-87332512022-01-06 Adapting Urban Transport Planning to the COVID-19 Pandemic: An Integrated Fermatean Fuzzy Model Simić, Vladimir Ivanović, Ivan Đorić, Vladimir Torkayesh, Ali Ebadi Sustain Cities Soc Article The critical worldwide problem of adapting urban transport planning to COVID-19 is for the first time comprehensively addressed and solved in this study. It primarily aims to help transport planners increase the resilience of transport systems. Firstly, a multi-level decision-making hierarchy structure based on four main criteria and 17 sub-criteria is introduced for relevant stakeholders to provide a practical framework for assessing existing transport plans. Then, a three-stage integrated Fermatean fuzzy model for adapting urban transport planning to the pandemic is presented. The model hybridizes the method based on the removal effects of criteria (MEREC) and combined compromise solution (CoCoSo) method into a unique methodological framework under the Fermatean fuzzy environment. A case study provides decision-making guidelines on how to adapt transport plans to COVID-19 in the real-world context of Belgrade, Serbia. The research findings show that the pandemic significantly changed the priorities of transport planning strategies and measures. “Non-motorized travel” is now the best alternative since its numerous short-term measures lead to better transport service. The major advantages of the introduced model are higher flexibility and a more precise fusion of experts’ preference information. The integrated Fermatean fuzzy model could be used for adapting other emerging problems to COVID-19. Elsevier Ltd. 2022-04 2022-01-06 /pmc/articles/PMC8733251/ /pubmed/35013703 http://dx.doi.org/10.1016/j.scs.2022.103669 Text en © 2022 Elsevier Ltd. 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 Simić, Vladimir Ivanović, Ivan Đorić, Vladimir Torkayesh, Ali Ebadi Adapting Urban Transport Planning to the COVID-19 Pandemic: An Integrated Fermatean Fuzzy Model |
title | Adapting Urban Transport Planning to the COVID-19 Pandemic: An Integrated Fermatean Fuzzy Model |
title_full | Adapting Urban Transport Planning to the COVID-19 Pandemic: An Integrated Fermatean Fuzzy Model |
title_fullStr | Adapting Urban Transport Planning to the COVID-19 Pandemic: An Integrated Fermatean Fuzzy Model |
title_full_unstemmed | Adapting Urban Transport Planning to the COVID-19 Pandemic: An Integrated Fermatean Fuzzy Model |
title_short | Adapting Urban Transport Planning to the COVID-19 Pandemic: An Integrated Fermatean Fuzzy Model |
title_sort | adapting urban transport planning to the covid-19 pandemic: an integrated fermatean fuzzy model |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8733251/ https://www.ncbi.nlm.nih.gov/pubmed/35013703 http://dx.doi.org/10.1016/j.scs.2022.103669 |
work_keys_str_mv | AT simicvladimir adaptingurbantransportplanningtothecovid19pandemicanintegratedfermateanfuzzymodel AT ivanovicivan adaptingurbantransportplanningtothecovid19pandemicanintegratedfermateanfuzzymodel AT đoricvladimir adaptingurbantransportplanningtothecovid19pandemicanintegratedfermateanfuzzymodel AT torkayeshaliebadi adaptingurbantransportplanningtothecovid19pandemicanintegratedfermateanfuzzymodel |