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Utilizing IoT to design a relief supply chain network for the SARS-COV-2 pandemic
The current universally challenging SARS-COV-2 pandemic has transcended all the social, logical, economic, and mortal boundaries regarding global operations. Although myriad global societies tried to address this issue, most of the employed efforts seem superficial and failed to deal with the proble...
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/PMC7902221/ https://www.ncbi.nlm.nih.gov/pubmed/33642961 http://dx.doi.org/10.1016/j.asoc.2021.107210 |
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author | Zahedi, Ali Salehi-Amiri, Amirhossein Smith, Neale R. Hajiaghaei-Keshteli, Mostafa |
author_facet | Zahedi, Ali Salehi-Amiri, Amirhossein Smith, Neale R. Hajiaghaei-Keshteli, Mostafa |
author_sort | Zahedi, Ali |
collection | PubMed |
description | The current universally challenging SARS-COV-2 pandemic has transcended all the social, logical, economic, and mortal boundaries regarding global operations. Although myriad global societies tried to address this issue, most of the employed efforts seem superficial and failed to deal with the problem, especially in the healthcare sector. On the other hand, the Internet of Things (IoT) has enabled healthcare system for both better understanding of the patient’s condition and appropriate monitoring in a remote fashion. However, there has always been a gap for utilizing this approach on the healthcare system especially in agitated condition of the pandemics. Therefore, in this study, we develop two innovative approaches to design a relief supply chain network is by using IoT to address multiple suspected cases during a pandemic like the SARS-COV-2 outbreak. The first approach (prioritizing approach) minimizes the maximum ambulances response time, while the second approach (allocating approach) minimizes the total critical response time. Each approach is validated and investigated utilizing several test problems and a real case in Iran as well. A set of efficient meta-heuristics and hybrid ones is developed to optimize the proposed models. The proposed approaches have shown their versatility in various harsh SARS-COV-2 pandemic situations being dealt with by managers. Finally, we compare the two proposed approaches in terms of response time and route optimization using a real case study in Iran. Implementing the proposed IoT-based methodology in three consecutive weeks, the results showed 35.54% decrease in the number of confirmed cases. |
format | Online Article Text |
id | pubmed-7902221 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-79022212021-02-24 Utilizing IoT to design a relief supply chain network for the SARS-COV-2 pandemic Zahedi, Ali Salehi-Amiri, Amirhossein Smith, Neale R. Hajiaghaei-Keshteli, Mostafa Appl Soft Comput Article The current universally challenging SARS-COV-2 pandemic has transcended all the social, logical, economic, and mortal boundaries regarding global operations. Although myriad global societies tried to address this issue, most of the employed efforts seem superficial and failed to deal with the problem, especially in the healthcare sector. On the other hand, the Internet of Things (IoT) has enabled healthcare system for both better understanding of the patient’s condition and appropriate monitoring in a remote fashion. However, there has always been a gap for utilizing this approach on the healthcare system especially in agitated condition of the pandemics. Therefore, in this study, we develop two innovative approaches to design a relief supply chain network is by using IoT to address multiple suspected cases during a pandemic like the SARS-COV-2 outbreak. The first approach (prioritizing approach) minimizes the maximum ambulances response time, while the second approach (allocating approach) minimizes the total critical response time. Each approach is validated and investigated utilizing several test problems and a real case in Iran as well. A set of efficient meta-heuristics and hybrid ones is developed to optimize the proposed models. The proposed approaches have shown their versatility in various harsh SARS-COV-2 pandemic situations being dealt with by managers. Finally, we compare the two proposed approaches in terms of response time and route optimization using a real case study in Iran. Implementing the proposed IoT-based methodology in three consecutive weeks, the results showed 35.54% decrease in the number of confirmed cases. Elsevier B.V. 2021-06 2021-02-24 /pmc/articles/PMC7902221/ /pubmed/33642961 http://dx.doi.org/10.1016/j.asoc.2021.107210 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 Zahedi, Ali Salehi-Amiri, Amirhossein Smith, Neale R. Hajiaghaei-Keshteli, Mostafa Utilizing IoT to design a relief supply chain network for the SARS-COV-2 pandemic |
title | Utilizing IoT to design a relief supply chain network for the SARS-COV-2 pandemic |
title_full | Utilizing IoT to design a relief supply chain network for the SARS-COV-2 pandemic |
title_fullStr | Utilizing IoT to design a relief supply chain network for the SARS-COV-2 pandemic |
title_full_unstemmed | Utilizing IoT to design a relief supply chain network for the SARS-COV-2 pandemic |
title_short | Utilizing IoT to design a relief supply chain network for the SARS-COV-2 pandemic |
title_sort | utilizing iot to design a relief supply chain network for the sars-cov-2 pandemic |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7902221/ https://www.ncbi.nlm.nih.gov/pubmed/33642961 http://dx.doi.org/10.1016/j.asoc.2021.107210 |
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