Fuzzy evolutionary algorithms and neural networks in uncertain optimization problems

Abstract

This paper is devoted to the application of the evolutionary algorithms and artificial neural networks to uncertain optimization problems in which some parameters are described by fuzzy numbers. The special method of global optimization: Two-Stages Fuzzy Strategy (TSFS) for structures in uncertain conditions is proposed. As the first stage of the TSFS the fuzzy evolutionary algorithm is used. As the second stage the local optimization method with neuro-computing is proposed. The presented approach is applied in the identification problems of mechanical structures, in which material parameters and loadings are uncertain. To solve the direct problem the fuzzy boundary element method (FBEM) is used. Several numerical tests and examples are presented.