Development of adaptive genetic algorithms for neural network models multicriteria design

In this paper modifications of single- and multi-objective genetic algorithms are described and testing results of these approaches are presented. The gist of the algorithms is the use of the self-adaptation idea leading to reducing of the expert significance for the algorithm setting and expanding of GAs’ application capabilities. On the basis of offered methods the program system realizing the technique for neural network models design was developed. The effectiveness of all algorithms was investigated on a set of test problems.