A metaheuristic to support the distribution of COVID-19 vaccines
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Production |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-65132021000100704 |
Resumo: | Abstract Paper aims The aim is to develop a vaccine distribution routing model (VDRM) in order to support governments to mitigate the pandemic caused by COVID-19. Originality As far as we know, no metaheuristics has been developed for vaccine distribution, and specifically, to support the Brazilian government. Research method A metaheuristic is developed based on the combination and adaptation of GRASP (Greedy Randomized Adaptive Search Procedure) with VND (Variable Neighborhood Descent), considering different refinement operators. Finally, as a way of validating the model, a numerical application in the state of Pernambuco (Brazil) was performed. Main findings Metaheuristic proved to be effective for developing adequate planning for the allocation of ampoules with vaccines to combat COVID-19. Effective analysis was obtained in the evaluation of the proposed algorithm, both in terms of computational effort and the quality of the final solution. An efficiency of approximately 75% was obtained in relation to the current distribution procedure adopted by the state of Pernambuco. Implications for theory and practice To mitigate disease, adequate logistics for transporting and distributing vaccines is essential, especially in emergency situations to face pandemic crises. Thus, the developed metaheuristic can support governments and companies in any situation demanded, making the decision of how the distribution of the ampoules will be more agile. |
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A metaheuristic to support the distribution of COVID-19 vaccinesCOVID-19Vehicle routingGRASPVNDAbstract Paper aims The aim is to develop a vaccine distribution routing model (VDRM) in order to support governments to mitigate the pandemic caused by COVID-19. Originality As far as we know, no metaheuristics has been developed for vaccine distribution, and specifically, to support the Brazilian government. Research method A metaheuristic is developed based on the combination and adaptation of GRASP (Greedy Randomized Adaptive Search Procedure) with VND (Variable Neighborhood Descent), considering different refinement operators. Finally, as a way of validating the model, a numerical application in the state of Pernambuco (Brazil) was performed. Main findings Metaheuristic proved to be effective for developing adequate planning for the allocation of ampoules with vaccines to combat COVID-19. Effective analysis was obtained in the evaluation of the proposed algorithm, both in terms of computational effort and the quality of the final solution. An efficiency of approximately 75% was obtained in relation to the current distribution procedure adopted by the state of Pernambuco. Implications for theory and practice To mitigate disease, adequate logistics for transporting and distributing vaccines is essential, especially in emergency situations to face pandemic crises. Thus, the developed metaheuristic can support governments and companies in any situation demanded, making the decision of how the distribution of the ampoules will be more agile.Associação Brasileira de Engenharia de Produção2021-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-65132021000100704Production v.31 2021reponame:Productioninstname:Associação Brasileira de Engenharia de Produção (ABEPRO)instacron:ABEPRO10.1590/0103-6513.20210031info:eu-repo/semantics/openAccessRodrigues,Augusto José da SilvaLima,Gabriel Lopeseng2021-10-07T00:00:00Zoai:scielo:S0103-65132021000100704Revistahttps://www.scielo.br/j/prod/https://old.scielo.br/oai/scielo-oai.php||production@editoracubo.com.br1980-54110103-6513opendoar:2021-10-07T00:00Production - Associação Brasileira de Engenharia de Produção (ABEPRO)false |
dc.title.none.fl_str_mv |
A metaheuristic to support the distribution of COVID-19 vaccines |
title |
A metaheuristic to support the distribution of COVID-19 vaccines |
spellingShingle |
A metaheuristic to support the distribution of COVID-19 vaccines Rodrigues,Augusto José da Silva COVID-19 Vehicle routing GRASP VND |
title_short |
A metaheuristic to support the distribution of COVID-19 vaccines |
title_full |
A metaheuristic to support the distribution of COVID-19 vaccines |
title_fullStr |
A metaheuristic to support the distribution of COVID-19 vaccines |
title_full_unstemmed |
A metaheuristic to support the distribution of COVID-19 vaccines |
title_sort |
A metaheuristic to support the distribution of COVID-19 vaccines |
author |
Rodrigues,Augusto José da Silva |
author_facet |
Rodrigues,Augusto José da Silva Lima,Gabriel Lopes |
author_role |
author |
author2 |
Lima,Gabriel Lopes |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Rodrigues,Augusto José da Silva Lima,Gabriel Lopes |
dc.subject.por.fl_str_mv |
COVID-19 Vehicle routing GRASP VND |
topic |
COVID-19 Vehicle routing GRASP VND |
description |
Abstract Paper aims The aim is to develop a vaccine distribution routing model (VDRM) in order to support governments to mitigate the pandemic caused by COVID-19. Originality As far as we know, no metaheuristics has been developed for vaccine distribution, and specifically, to support the Brazilian government. Research method A metaheuristic is developed based on the combination and adaptation of GRASP (Greedy Randomized Adaptive Search Procedure) with VND (Variable Neighborhood Descent), considering different refinement operators. Finally, as a way of validating the model, a numerical application in the state of Pernambuco (Brazil) was performed. Main findings Metaheuristic proved to be effective for developing adequate planning for the allocation of ampoules with vaccines to combat COVID-19. Effective analysis was obtained in the evaluation of the proposed algorithm, both in terms of computational effort and the quality of the final solution. An efficiency of approximately 75% was obtained in relation to the current distribution procedure adopted by the state of Pernambuco. Implications for theory and practice To mitigate disease, adequate logistics for transporting and distributing vaccines is essential, especially in emergency situations to face pandemic crises. Thus, the developed metaheuristic can support governments and companies in any situation demanded, making the decision of how the distribution of the ampoules will be more agile. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-01-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-65132021000100704 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-65132021000100704 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/0103-6513.20210031 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Associação Brasileira de Engenharia de Produção |
publisher.none.fl_str_mv |
Associação Brasileira de Engenharia de Produção |
dc.source.none.fl_str_mv |
Production v.31 2021 reponame:Production instname:Associação Brasileira de Engenharia de Produção (ABEPRO) instacron:ABEPRO |
instname_str |
Associação Brasileira de Engenharia de Produção (ABEPRO) |
instacron_str |
ABEPRO |
institution |
ABEPRO |
reponame_str |
Production |
collection |
Production |
repository.name.fl_str_mv |
Production - Associação Brasileira de Engenharia de Produção (ABEPRO) |
repository.mail.fl_str_mv |
||production@editoracubo.com.br |
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1754213154831728640 |