Intelligent computational technique with CGA approach for optimal solutions

Abstract

In this paper, Continuous Genetic Algorithms (CGAs) are used as an intelligent computational technique to provide a problem optimal solution. The problem is formulated as an optimization problem by the direct minimization of the performance index subject to constraints, and is then solved using a CGA. The presented approach has some advantages over the other existing direct and indirect methods which either suffer from low accuracy or lack of robustness. One advantage is that our method can be applied without any limitation on the nature of the problem (number of control signals and mesh points). Another advantage is that high accuracy can be achieved in that the performance index is globally minimized.