Tracking the Heritage of Genes in Evolutionary Algorithms

This paper aims to introduce a methodology to trace the influence of the initial population of an evolutionary algorithm to the final population. The major challenge concerns tracking the heritage of multiple parent operators. In this paper, we propose a new encoding for tracking purposes. In addition, we propose modifications to the corresponding metrics for measuring the impact of individuals. With this approach, we provide several tools to not only track the influence of the initial population on the results but also to study the effects of different crossover and mutation operators. In our experiments, we evaluate the differences between two selected crossover and mutation operators and provide insight into the proposed approach.