GA with fuzzy inference system

Abstract

Applications of genetic algorithms (GA) for optimisation problems are widely known as well as their advantages and disadvantages compared with classical numerical methods. In practical tests, GA appears a robust method with a broad range of applications. The determination of GA parameters could be complicated. Therefore for some real-life applications, several empirical observations of an experienced expert are needed to define these parameters. This fact degrades the applicability of a GA for most of the real-world problems and users. Therefore, this article discusses some possibilities with setting GA parameters. The setting method of GA parameters is based on the fuzzy control of values of GA parameters. The feedback for the fuzzy control of GA parameters is realized by virtue of the behavior of some GA characteristics. The goal of this article is to present the conception of the solution and some new ideas.