Abstract
Although the genetic algorithm (GA) is powerful and not limited by restrictive assumptions about search space of optimization problems, it has a convergency problem when it is used to find the optimum point with high accuracy. The object of developing an intelligent GA is to improve this weakness. In this paper, the optimization procedures of an intelligent GA are investigated, the advantages of the intelligent GA in improving the weakness in selecting GA parameters are confirmed.