Application of an iterative method and an evolutionary algorithm in fuzzy optimization

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dc.contributor.authorSilva, Ricardo Coelho
dc.contributor.authorCantão, Luiza A.P. [UNESP]
dc.contributor.authorYamakami, Akebo
dc.contributor.institutionUniversidade de São Paulo (USP)
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionUniversidade Estadual de Campinas (UNICAMP)
dc.date.accessioned2014-05-27T11:26:29Z
dc.date.available2014-05-27T11:26:29Z
dc.date.issued2012-05-01
dc.description.abstractThis work develops two approaches based on the fuzzy set theory to solve a class of fuzzy mathematical optimization problems with uncertainties in the objective function and in the set of constraints. The first approach is an adaptation of an iterative method that obtains cut levels and later maximizes the membership function of fuzzy decision making using the bound search method. The second one is a metaheuristic approach that adapts a standard genetic algorithm to use fuzzy numbers. Both approaches use a decision criterion called satisfaction level that reaches the best solution in the uncertain environment. Selected examples from the literature are presented to compare and to validate the efficiency of the methods addressed, emphasizing the fuzzy optimization problem in some import-export companies in the south of Spain. © 2012 Brazilian Operations Research Society.en
dc.description.affiliationInstitute of Science and Technology Federal University of São Paulo UNIFESP, Rua Talim, 330, 12231-280 São José dos Campos, SP
dc.description.affiliationEnvironmental Engineering Department São Paulo State University Sorocaba, SP
dc.description.affiliationDepartment of Telematics School of Electrical and Computer Engineering University of Campinas - UNICAMP, Av. Albert Einstein, 400, 13083-852 Campinas, SP
dc.description.affiliationUnespEnvironmental Engineering Department São Paulo State University Sorocaba, SP
dc.format.extent315-329
dc.identifierhttp://dx.doi.org/10.1590/S0101-74382012005000018
dc.identifier.citationPesquisa Operacional, v. 32, n. 2, p. 315-329, 2012.
dc.identifier.doi10.1590/S0101-74382012005000018
dc.identifier.file2-s2.0-84866431896.pdf
dc.identifier.issn0101-7438
dc.identifier.issn1678-5142
dc.identifier.scieloS0101-74382012005000018
dc.identifier.scopus2-s2.0-84866431896
dc.identifier.urihttp://hdl.handle.net/11449/73304
dc.language.isoeng
dc.relation.ispartofPesquisa Operacional
dc.relation.ispartofsjr0,365
dc.rights.accessRightsAcesso aberto
dc.sourceScopus
dc.subjectCut levels
dc.subjectFuzzy numbers
dc.subjectFuzzy optimization
dc.subjectGenetic algorithms
dc.titleApplication of an iterative method and an evolutionary algorithm in fuzzy optimizationen
dc.typeArtigo
dcterms.licensehttp://www.scielo.br/revistas/pope/paboutj.htm
unesp.campusUniversidade Estadual Paulista (Unesp), Instituto de Ciência e Tecnologia, Sorocabapt

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Artigos - Engenharia Ambiental - Sorocaba