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A two-stage decision-support approach for improving sustainable last-mile cold chain logistics operations of COVID-19 vaccines
The COVID-19 pandemic has become a global health and humanitarian crisis that catastrophically affects many industries. To control the disease spread and restore normal lives, mass vaccination is considered the most effective way. However, the sustainable last-mile cold chain logistics operations of...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9392992/ https://www.ncbi.nlm.nih.gov/pubmed/36035453 http://dx.doi.org/10.1007/s10479-022-04906-x |
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author | Andoh, Eugenia Ama Yu, Hao |
author_facet | Andoh, Eugenia Ama Yu, Hao |
author_sort | Andoh, Eugenia Ama |
collection | PubMed |
description | The COVID-19 pandemic has become a global health and humanitarian crisis that catastrophically affects many industries. To control the disease spread and restore normal lives, mass vaccination is considered the most effective way. However, the sustainable last-mile cold chain logistics operations of COVID-19 vaccines is a complex short-term planning problem that faces many practical challenges, e.g., low-temperature storage and transportation, supply uncertainty at the early stage, etc. To tackle these challenges, a two-stage decision-support approach is proposed in this paper, which integrates both route optimization and advanced simulation to improve the sustainable performance of last-mile vaccine cold chain logistics operations. Through a real-world case study in Norway during December 2020 and March 2021, the analytical results revealed that the logistics network structure, fleet size, and the composition of heterogeneous vehicles might yield significant impacts on the service level, transportation cost, and CO(2) emissions of last-mile vaccine cold chain logistics operations. |
format | Online Article Text |
id | pubmed-9392992 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-93929922022-08-22 A two-stage decision-support approach for improving sustainable last-mile cold chain logistics operations of COVID-19 vaccines Andoh, Eugenia Ama Yu, Hao Ann Oper Res Original Research The COVID-19 pandemic has become a global health and humanitarian crisis that catastrophically affects many industries. To control the disease spread and restore normal lives, mass vaccination is considered the most effective way. However, the sustainable last-mile cold chain logistics operations of COVID-19 vaccines is a complex short-term planning problem that faces many practical challenges, e.g., low-temperature storage and transportation, supply uncertainty at the early stage, etc. To tackle these challenges, a two-stage decision-support approach is proposed in this paper, which integrates both route optimization and advanced simulation to improve the sustainable performance of last-mile vaccine cold chain logistics operations. Through a real-world case study in Norway during December 2020 and March 2021, the analytical results revealed that the logistics network structure, fleet size, and the composition of heterogeneous vehicles might yield significant impacts on the service level, transportation cost, and CO(2) emissions of last-mile vaccine cold chain logistics operations. Springer US 2022-08-21 /pmc/articles/PMC9392992/ /pubmed/36035453 http://dx.doi.org/10.1007/s10479-022-04906-x Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 | Original Research Andoh, Eugenia Ama Yu, Hao A two-stage decision-support approach for improving sustainable last-mile cold chain logistics operations of COVID-19 vaccines |
title | A two-stage decision-support approach for improving sustainable last-mile cold chain logistics operations of COVID-19 vaccines |
title_full | A two-stage decision-support approach for improving sustainable last-mile cold chain logistics operations of COVID-19 vaccines |
title_fullStr | A two-stage decision-support approach for improving sustainable last-mile cold chain logistics operations of COVID-19 vaccines |
title_full_unstemmed | A two-stage decision-support approach for improving sustainable last-mile cold chain logistics operations of COVID-19 vaccines |
title_short | A two-stage decision-support approach for improving sustainable last-mile cold chain logistics operations of COVID-19 vaccines |
title_sort | two-stage decision-support approach for improving sustainable last-mile cold chain logistics operations of covid-19 vaccines |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9392992/ https://www.ncbi.nlm.nih.gov/pubmed/36035453 http://dx.doi.org/10.1007/s10479-022-04906-x |
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