1. Repositório Institucional da UFMG
  2. Trabalhos Acadêmicos
  3. Dissertações e Teses
  4. Pós-Graduação em Ciência da Computação
  5. Teses de Doutorado
Please use this identifier to cite or link to this item: http://hdl.handle.net/1843/ESBF-AYUMW2
Full metadata record
DC FieldValueLanguage
dc.contributor.advisor1Thiago Ferreira de Noronhapt_BR
dc.contributor.advisor-co1Andrea Cynthia Santospt_BR
dc.contributor.referee1Andrea Cynthia Santospt_BR
dc.contributor.referee2Sebastián Alberto Urrutiapt_BR
dc.contributor.referee3Christophe Duhamelpt_BR
dc.contributor.referee4Philippe Yves Paul Michelonpt_BR
dc.creatorAmadeu Almeida Cocopt_BR
dc.date.accessioned2019-08-10T00:29:42Z-
dc.date.available2019-08-10T00:29:42Z-
dc.date.issued2017-10-06pt_BR
dc.identifier.urihttp://hdl.handle.net/1843/ESBF-AYUMW2-
dc.description.resumoTwo 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.pt_BR
dc.languagePortuguêspt_BR
dc.publisherUniversidade Federal de Minas Geraispt_BR
dc.publisher.initialsUFMGpt_BR
dc.rightsAcesso Abertopt_BR
dc.subjectAlgoritmospt_BR
dc.subjectLogísticapt_BR
dc.subjectMeta-heurísticaspt_BR
dc.subjectPesquisa Operacionalpt_BR
dc.subjectOtimização Combinatóriapt_BR
dc.subject.otherAlgorítmospt_BR
dc.subject.otherLogísticapt_BR
dc.subject.otherOtimização combinatóriapt_BR
dc.subject.otherPesquisa operacionalpt_BR
dc.subject.otherComputaçãopt_BR
dc.subject.otherMeta-heurísticaspt_BR
dc.titleRobust covering problems: formulations, algorithms and applicationpt_BR
dc.typeTese de Doutoradopt_BR
Appears in Collections:Teses de Doutorado

Files in This Item:
File Description SizeFormat 
amadeualmeidacoco.pdf968.67 kBAdobe PDFView/Open
Show simple item record


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.