Analysis of speciation and niching in the multi-niche crowding GA

AbstractThe multi-niche crowding genetic algorithm (MNC GA) has demonstrated its ability to maintain population diversity and stable subpopulations while allowing different species to evolve naturally in different niches of the fitness landscape. These properties are a consequence, in part, to the effect of crowding selection and worst among most similar replacement genetic operators. In this paper we take a closer look at these genetic operators and present mathematical results that show their effect on the population when used in the MNC GA. We also present some guidelines about the parameter values to use in these genetic operators to achieve the desired niching pressure during a run. We conclude with a list of unexplored avenues that might be helpful in a future analysis of the behaviour of the MNC GA