Robust covering problems: formulations, algorithms and application

Two robust optimization NP-Hard problems are studied in this thesis: the min-max regret WSCP and the min-max regret MCLP. The uncertain data in these problems is modeled by intervals and only the minimum and maximum values for each interval are known. While the min-max regret WSCP is still a theoret...

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Detalles Bibliográficos
Autor: Amadeu Almeida Coco
Tipo de recurso: tesis doctoral
Estado:Versión publicada
Fecha de publicación:2017
País:Brasil
Institución:Universidade Federal de Minas Gerais (UFMG)
Repositorio:Repositório Institucional da UFMG
Idioma:portugués
OAI Identifier:oai:repositorio.ufmg.br:1843/ESBF-AYUMW2
Acceso en línea:http://hdl.handle.net/1843/ESBF-AYUMW2
Access Level:acceso abierto
Palabra clave:Algoritmos
Logística
Meta-heurísticas
Pesquisa Operacional
Otimização Combinatória
Algorítmos
Otimização combinatória
Pesquisa operacional
Computação
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network_name_str Brasil
repository_id_str
spelling Robust covering problems: formulations, algorithms and applicationAlgoritmosLogísticaMeta-heurísticasPesquisa OperacionalOtimização CombinatóriaAlgorítmosLogísticaOtimização combinatóriaPesquisa operacionalComputaçãoMeta-heurísticasTwo robust optimization NP-Hard problems are studied in this thesis: the min-max regret WSCP and the min-max regret MCLP. The uncertain data in these problems is modeled by intervals and only the minimum and maximum values for each interval are known. While the min-max regret WSCP is still a theoretical problem, the min-max regret MCLP has an application in disaster logistics which is investigated in this thesis. Four mathematical formulations, three exact algorithms and five heuristics were developed and applied to both problems. Computational experiments showed that the exact algorithms efficiently solved 14 out of 75 instances generated to the min-max regret WSCP and all realistic instances created to the min-max regret MCLP. For the simulated instances that was not solved to optimally in both problems, the heuristics developed in this thesis found solutions, as good as, or better than the best exact algorithm in almost all instance.Universidade Federal de Minas GeraisUFMGThiago Ferreira de NoronhaAndrea Cynthia SantosAndrea Cynthia SantosSebastián Alberto UrrutiaChristophe DuhamelPhilippe Yves Paul Michelon2019-08-10T00:29:42Z2019-08-10T00:29:42Z2017-10-06info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdfhttp://hdl.handle.net/1843/ESBF-AYUMW2info:eu-repo/semantics/openAccessporreponame:Repositório Institucional da UFMGinstname:Universidade Federal de Minas Gerais (UFMG)instacron:UFMGAmadeu Almeida Coco2019-11-14T11:33:51Zoai:repositorio.ufmg.br:1843/ESBF-AYUMW2Repositório InstitucionalPUBhttps://repositorio.ufmg.br/oairepositorio@ufmg.bropendoar:2019-11-14T11:33:51Repositório Institucional da UFMG - Universidade Federal de Minas Gerais (UFMG)false
dc.title.none.fl_str_mv Robust covering problems: formulations, algorithms and application
title Robust covering problems: formulations, algorithms and application
spellingShingle Robust covering problems: formulations, algorithms and application
Amadeu Almeida Coco
Algoritmos
Logística
Meta-heurísticas
Pesquisa Operacional
Otimização Combinatória
Algorítmos
Logística
Otimização combinatória
Pesquisa operacional
Computação
Meta-heurísticas
title_short Robust covering problems: formulations, algorithms and application
title_full Robust covering problems: formulations, algorithms and application
title_fullStr Robust covering problems: formulations, algorithms and application
title_full_unstemmed Robust covering problems: formulations, algorithms and application
title_sort Robust covering problems: formulations, algorithms and application
dc.creator.none.fl_str_mv Amadeu Almeida Coco
author Amadeu Almeida Coco
author_facet Amadeu Almeida Coco
author_role author
dc.contributor.none.fl_str_mv Thiago Ferreira de Noronha
Andrea Cynthia Santos
Andrea Cynthia Santos
Sebastián Alberto Urrutia
Christophe Duhamel
Philippe Yves Paul Michelon
dc.subject.por.fl_str_mv Algoritmos
Logística
Meta-heurísticas
Pesquisa Operacional
Otimização Combinatória
Algorítmos
Logística
Otimização combinatória
Pesquisa operacional
Computação
Meta-heurísticas
topic Algoritmos
Logística
Meta-heurísticas
Pesquisa Operacional
Otimização Combinatória
Algorítmos
Logística
Otimização combinatória
Pesquisa operacional
Computação
Meta-heurísticas
description Two robust optimization NP-Hard problems are studied in this thesis: the min-max regret WSCP and the min-max regret MCLP. The uncertain data in these problems is modeled by intervals and only the minimum and maximum values for each interval are known. While the min-max regret WSCP is still a theoretical problem, the min-max regret MCLP has an application in disaster logistics which is investigated in this thesis. Four mathematical formulations, three exact algorithms and five heuristics were developed and applied to both problems. Computational experiments showed that the exact algorithms efficiently solved 14 out of 75 instances generated to the min-max regret WSCP and all realistic instances created to the min-max regret MCLP. For the simulated instances that was not solved to optimally in both problems, the heuristics developed in this thesis found solutions, as good as, or better than the best exact algorithm in almost all instance.
publishDate 2017
dc.date.none.fl_str_mv 2017-10-06
2019-08-10T00:29:42Z
2019-08-10T00:29:42Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/doctoralThesis
format doctoralThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/1843/ESBF-AYUMW2
url http://hdl.handle.net/1843/ESBF-AYUMW2
dc.language.iso.fl_str_mv por
language por
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 Universidade Federal de Minas Gerais
UFMG
publisher.none.fl_str_mv Universidade Federal de Minas Gerais
UFMG
dc.source.none.fl_str_mv reponame:Repositório Institucional da UFMG
instname:Universidade Federal de Minas Gerais (UFMG)
instacron:UFMG
instname_str Universidade Federal de Minas Gerais (UFMG)
instacron_str UFMG
institution UFMG
reponame_str Repositório Institucional da UFMG
collection Repositório Institucional da UFMG
repository.name.fl_str_mv Repositório Institucional da UFMG - Universidade Federal de Minas Gerais (UFMG)
repository.mail.fl_str_mv repositorio@ufmg.br
_version_ 1853663071317262336
score 15.301629

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