A new population based adaptive domination change mechanism for diploid genetic algorithms in dynamic environments

Abstract

In this paper, an adaptive domination change mechanism for diploid genetic algorithms with discrete representations is presented. It is aimed at improving the performance of existing diploid genetic algorithms in changing environments. Diploidy acts as a source of diversity in the gene pool while the adaptive domination mechanism guides the phenotype towards an optimum. The combined effect of diploidy and the adaptive domination forms a balance between exploration and exploitation. The dominance characteristic of each locus in the population is adapted through feedback from the ongoing search process. A dynamic bit matching benchmark is used to perform controlled experiments. Controlled changes to implement different levels of change severities and frequencies are used. The testing phase consists of four stages. In the first stage, the benefits of the adaptive domination mechanism are shown by testing it against previously proposed diploid approaches. In the second stage, the same adaptive approach is applied to a haploid genetic algorithm to show the effect of the diploidy on the performance of the proposed approach. In the third stage, the levels of diversity introduced by diploidy on the genotype and maintained by the adaptive domination mechanism on the phenotype are explored. In the fourth stage, tests are performed to examine the robustness of the chosen approaches against different mutation rates. Currently, the dominance change mechanism can be applied to di-allelic or multiallelic discrete representations and promising results are obtained as a result of the tests performed.