The smart waste collection routing problem: alternative operational management approaches
Autor(a) principal: | |
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Data de Publicação: | 2018 |
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/10071/15661 |
Resumo: | Waste collection is nowadays an increasingly important business. However, it is often an inefficient op- eration due to the high uncertainty associated with the real waste bins’ fill-levels. To deal with such uncertainty the use of sensors to transmit real time information is seen as possible solution. But, in order to improve operations’ efficiency, the sensors’ usage must be combined with optimization procedures that inform on the optimal collection routes to operationalize, so as to guarantee a maximization of the waste collected while also minimizing transportation costs. The present work explores this challenge and studies three operational management approaches to define dynamic optimal routes, considering the access to real-time information on the bins’ fill-levels. A real case study is solved and important results were found where significant profit improvements are observed when compared to the real operation. This shows the potential of the proposed approaches to build an expert system, which can support the operations manager’s decisions. |
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The smart waste collection routing problem: alternative operational management approachesReal-time dataSensorsSmart collectionOptimizationWaste managementDynamic routingWaste collection is nowadays an increasingly important business. However, it is often an inefficient op- eration due to the high uncertainty associated with the real waste bins’ fill-levels. To deal with such uncertainty the use of sensors to transmit real time information is seen as possible solution. But, in order to improve operations’ efficiency, the sensors’ usage must be combined with optimization procedures that inform on the optimal collection routes to operationalize, so as to guarantee a maximization of the waste collected while also minimizing transportation costs. The present work explores this challenge and studies three operational management approaches to define dynamic optimal routes, considering the access to real-time information on the bins’ fill-levels. A real case study is solved and important results were found where significant profit improvements are observed when compared to the real operation. This shows the potential of the proposed approaches to build an expert system, which can support the operations manager’s decisions.Pergamon/Elsevier2018-04-19T13:36:13Z2019-10-19T00:00:00Z2018-01-01T00:00:00Z20182019-03-08T10:37:19Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10071/15661eng0957-417410.1016/j.eswa.2018.03.001Ramos, T. R. P.de Morais, C. S.Barbosa-Póvoa, A. P.info: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:RCAAP2023-11-09T17:43:50Zoai:repositorio.iscte-iul.pt:10071/15661Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:20:41.247035Repositório 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 |
The smart waste collection routing problem: alternative operational management approaches |
title |
The smart waste collection routing problem: alternative operational management approaches |
spellingShingle |
The smart waste collection routing problem: alternative operational management approaches Ramos, T. R. P. Real-time data Sensors Smart collection Optimization Waste management Dynamic routing |
title_short |
The smart waste collection routing problem: alternative operational management approaches |
title_full |
The smart waste collection routing problem: alternative operational management approaches |
title_fullStr |
The smart waste collection routing problem: alternative operational management approaches |
title_full_unstemmed |
The smart waste collection routing problem: alternative operational management approaches |
title_sort |
The smart waste collection routing problem: alternative operational management approaches |
author |
Ramos, T. R. P. |
author_facet |
Ramos, T. R. P. de Morais, C. S. Barbosa-Póvoa, A. P. |
author_role |
author |
author2 |
de Morais, C. S. Barbosa-Póvoa, A. P. |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Ramos, T. R. P. de Morais, C. S. Barbosa-Póvoa, A. P. |
dc.subject.por.fl_str_mv |
Real-time data Sensors Smart collection Optimization Waste management Dynamic routing |
topic |
Real-time data Sensors Smart collection Optimization Waste management Dynamic routing |
description |
Waste collection is nowadays an increasingly important business. However, it is often an inefficient op- eration due to the high uncertainty associated with the real waste bins’ fill-levels. To deal with such uncertainty the use of sensors to transmit real time information is seen as possible solution. But, in order to improve operations’ efficiency, the sensors’ usage must be combined with optimization procedures that inform on the optimal collection routes to operationalize, so as to guarantee a maximization of the waste collected while also minimizing transportation costs. The present work explores this challenge and studies three operational management approaches to define dynamic optimal routes, considering the access to real-time information on the bins’ fill-levels. A real case study is solved and important results were found where significant profit improvements are observed when compared to the real operation. This shows the potential of the proposed approaches to build an expert system, which can support the operations manager’s decisions. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-04-19T13:36:13Z 2018-01-01T00:00:00Z 2018 2019-10-19T00:00:00Z 2019-03-08T10:37:19Z |
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/10071/15661 |
url |
http://hdl.handle.net/10071/15661 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
0957-4174 10.1016/j.eswa.2018.03.001 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Pergamon/Elsevier |
publisher.none.fl_str_mv |
Pergamon/Elsevier |
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 |
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1799134767223930880 |