A genetic algorithm for multiobjective optimization problems with fuzzy constraints

Authors:
Luciano de Moura;Akebo Yamakami;Tatiane R. Bonfim
Affiliations:
Department of Telematics School of Electrical and Computer Engineering University of Campinas Campinas - SP, Brazil;Department of Telematics School of Electrical and Computer Engineering University of Campinas Campinas - SP, Brazil;Department of Telematics School of Electrical and Computer Engineering University of Campinas Campinas - SP, Brazil
Venue:
Second international workshop on Intelligent systems design and application
Year:
2002

Citing 4
Cited 0

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Abstract

Fuzzy multiobjective optimization methods have been extensively applied to the modeling of real processes under influence of uncertainties. We propose a genetic algorithm based on a stable population technique to deal with the problem of fuzzy constraints. A set of optimization problems was used to test the algorithm and it proved to be very flexible and efficient.