Genetic strategy with gate change function

In this paper, a new genetic strategy is presented for optimizing multimodal functions with an arbitrary distribution of solutions. In this algorithm, a gate change function (GCF) is developed to aid in constructing a subparent space. Based on the use of GCF and the cooperation between parents and subparents, the strategy leads to an efficient solution of the problem. The simulation results, given in this paper, show that this algorithm finds all the solutions of a problem with less computation time than that of simple genetic algorithms