Random State Genetic Algorithm
Résumé
Following earlier results, the purpose of this paper is to show a new evolutionary algorithm whose parameters are moving in ranges defined by experiments. That is to say, no parameters must be fixed at the beginning of the course of generations. Comparing the performance of two methods, we arrive to the conclusion that the random often is a better way.