Genetic operators in a dual genetic algorithm

Abstract

It is not clear that the current distinction between crossover and mutation is necessary. We show that it is possible to implement one and only one general operator which can specialize crossover or mutation operators. We investigate this alternative. Our approach consists in inserting doubles in the population of chromosomes. This article argues that explicit mutations are unnecessary. Indeed, in dGAs without a mutation operator, chromosomes undergo the mutation effect. The dual genetic search provides a source of power for searching in a changing environment. Within this paper, a first effort is presented towards incorporating the feature of self-adaptation into GAs by using adaptive mutation rates. Finally, we study the effects of explicit mutation on a dual search space. We show that a contraction of the Hamming distance is induced from mutation. As a consequence, a dGA allows to increase the capabilities of evolution on rugged fitness landscapes.