Diversity control based on population heterozygosity dynamics

Maintaining the population diversity in genetic algorithms (GAs), or minimize its loss, may benefit the evolutionary process in several ways. The premature convergence may lead the GA to a non-optimal result, that is, converging to a local optimum. Specially in dynamic problems, the diversity preservation is a crucial issue. In this work, a study of different diversity models based on several works has been made. From these models a diversity reference-model has been created in order to enhance diversity-reference adaptive control (DRAC) [20] performance. This new version of DRAC method was evaluated in case studies using a dynamic test functions presented in [26]. The validation of the proposed adaptive parameter control method was performed comparing its performance with SGA and other diversity-based algorithm.