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

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

Author Silva, Ricardo Coelho Autor UNIFESP Google Scholar
Cantão, Luiza A.p. Google Scholar
Yamakami, Akebo Google Scholar
Institution Universidade Federal de São Paulo (UNIFESP)
Universidade Estadual Paulista (UNESP)
Universidade Estadual de Campinas (UNICAMP)
Abstract 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.
Keywords fuzzy numbers
cut levels
fuzzy optimization
genetic algorithms
Language English
Date 2012-08-01
Published in Pesquisa Operacional. Sociedade Brasileira de Pesquisa Operacional, v. 32, n. 2, p. 315-329, 2012.
ISSN 0101-7438 (Sherpa/Romeo)
Publisher Sociedade Brasileira de Pesquisa Operacional
Extent 315-329
Access rights Open access Open Access
Type Article
SciELO ID S0101-74382012000200004 (statistics in SciELO)

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