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

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

Autor Silva, Ricardo Coelho Autor UNIFESP Google Scholar
Cantão, Luiza A.p. Google Scholar
Yamakami, Akebo Google Scholar
Instituição Universidade Federal de São Paulo (UNIFESP)
Universidade Estadual Paulista (UNESP)
Universidade Estadual de Campinas (UNICAMP)
Resumo This 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.
Palavra-chave fuzzy numbers
cut levels
fuzzy optimization
genetic algorithms
Idioma Inglês
Data de publicação 2012-08-01
Publicado em Pesquisa Operacional. Sociedade Brasileira de Pesquisa Operacional, v. 32, n. 2, p. 315-329, 2012.
ISSN 0101-7438 (Sherpa/Romeo)
Publicador Sociedade Brasileira de Pesquisa Operacional
Extensão 315-329
Fonte http://dx.doi.org/10.1590/S0101-74382012005000018
Direito de acesso Acesso aberto Open Access
Tipo Artigo
SciELO S0101-74382012000200004 (estatísticas na SciELO)
Endereço permanente http://repositorio.unifesp.br/handle/11600/7250

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