Using a Meta-GA for parametric optimization of simple gas in the computational chemistry domain
Proceedings of the 12th annual conference on Genetic and evolutionary computation
An exact schema theorem for adaptive genetic algorithm and its application to machine cell formation
Expert Systems with Applications: An International Journal
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The study of Genetics Algorithms (GAs) with finite population size requires the stochastic treatment of evolution. In this study, we examined effects of genetic fluctuations on the performance of GA calculations. We considered the roles of mutation by using the stochastic schema theory within the framework of the Wright-Fisher model of Markov processes. The success probability of obtaining the optimum solution was investigated experimentally and theoretically. We noticed that mutation has effects of increasing the success probabilities. We also noticed crossover brings the population a good effect in results of GA.