Adaptive control of the mutation probability by fuzzy logic controllers

Abstract

A problem in the use of genetic algorithms is premature convergence, a premature stagnation of the search caused by the lack of population diversity. The mutation operator is the one responsible for the generation of diversity and therefore may be considered to be an important element in solving this problem. A solution adopted involves the control, throughout the run, of the parameter that determines its operation: the mutation probability. In this paper, we study an adaptive approach for the control of the mutation probability based on the application of fuzzy logic controllers. Experimental results show that this technique consistently outperforms other mechanisms presented in the genetic algorithm literature for controlling this genetic algorithm parameter.