Optimal Emergency Vehicles Location: an approach considering the hierarchy and substitutability of resources
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10316/95306 https://doi.org/10.1016/j.ejor.2020.03.067 |
Resumo: | Decisions on where to locate emergency vehicles have a crucial impact on the quality of the emergency service that is provided to populations, with consequences in terms of mortality and quality of life. It is important to guarantee the access of the population to emergency care, not forgetting the need to guarantee the best possible use of all available resources. In this work a new integer linear programming model is presented that aims at optimizing the location of emergency vehicles, considering in an explicit way the substitutability possibilities among vehicles of different types, taken into account the type of care they can provide. Moreover, the assignment of variables to emergency episodes is also explicitly considered which allows the model to be more accurate when calculating the expected coverage obtained. Both deterministic and stochastic models are presented. In the stochastic model, uncertainty regarding emergency episodes is represented by using scenarios. The model is applied to a dataset built considering all the features which are present in real data. |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Optimal Emergency Vehicles Location: an approach considering the hierarchy and substitutability of resourcesLocation OR in health services Emergency vehicles UncertaintyDecisions on where to locate emergency vehicles have a crucial impact on the quality of the emergency service that is provided to populations, with consequences in terms of mortality and quality of life. It is important to guarantee the access of the population to emergency care, not forgetting the need to guarantee the best possible use of all available resources. In this work a new integer linear programming model is presented that aims at optimizing the location of emergency vehicles, considering in an explicit way the substitutability possibilities among vehicles of different types, taken into account the type of care they can provide. Moreover, the assignment of variables to emergency episodes is also explicitly considered which allows the model to be more accurate when calculating the expected coverage obtained. Both deterministic and stochastic models are presented. In the stochastic model, uncertainty regarding emergency episodes is represented by using scenarios. The model is applied to a dataset built considering all the features which are present in real data.European Journal of Operational Research2020-03-25info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10316/95306http://hdl.handle.net/10316/95306https://doi.org/10.1016/j.ejor.2020.03.067enghttps://www.sciencedirect.com/science/article/abs/pii/S0377221720303003Nelas, JoséDias, Joana Diasinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2022-05-25T04:11:31Zoai:estudogeral.uc.pt:10316/95306Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T21:13:50.189833Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Optimal Emergency Vehicles Location: an approach considering the hierarchy and substitutability of resources |
title |
Optimal Emergency Vehicles Location: an approach considering the hierarchy and substitutability of resources |
spellingShingle |
Optimal Emergency Vehicles Location: an approach considering the hierarchy and substitutability of resources Nelas, José Location OR in health services Emergency vehicles Uncertainty |
title_short |
Optimal Emergency Vehicles Location: an approach considering the hierarchy and substitutability of resources |
title_full |
Optimal Emergency Vehicles Location: an approach considering the hierarchy and substitutability of resources |
title_fullStr |
Optimal Emergency Vehicles Location: an approach considering the hierarchy and substitutability of resources |
title_full_unstemmed |
Optimal Emergency Vehicles Location: an approach considering the hierarchy and substitutability of resources |
title_sort |
Optimal Emergency Vehicles Location: an approach considering the hierarchy and substitutability of resources |
author |
Nelas, José |
author_facet |
Nelas, José Dias, Joana Dias |
author_role |
author |
author2 |
Dias, Joana Dias |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Nelas, José Dias, Joana Dias |
dc.subject.por.fl_str_mv |
Location OR in health services Emergency vehicles Uncertainty |
topic |
Location OR in health services Emergency vehicles Uncertainty |
description |
Decisions on where to locate emergency vehicles have a crucial impact on the quality of the emergency service that is provided to populations, with consequences in terms of mortality and quality of life. It is important to guarantee the access of the population to emergency care, not forgetting the need to guarantee the best possible use of all available resources. In this work a new integer linear programming model is presented that aims at optimizing the location of emergency vehicles, considering in an explicit way the substitutability possibilities among vehicles of different types, taken into account the type of care they can provide. Moreover, the assignment of variables to emergency episodes is also explicitly considered which allows the model to be more accurate when calculating the expected coverage obtained. Both deterministic and stochastic models are presented. In the stochastic model, uncertainty regarding emergency episodes is represented by using scenarios. The model is applied to a dataset built considering all the features which are present in real data. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-03-25 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10316/95306 http://hdl.handle.net/10316/95306 https://doi.org/10.1016/j.ejor.2020.03.067 |
url |
http://hdl.handle.net/10316/95306 https://doi.org/10.1016/j.ejor.2020.03.067 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://www.sciencedirect.com/science/article/abs/pii/S0377221720303003 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
European Journal of Operational Research |
publisher.none.fl_str_mv |
European Journal of Operational Research |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
|
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1799134035293765632 |