Towards computing the parameters of the simple genetic algorithm

The problem of finding appropriate probabilities for crossover and mutation with respect to resampling may be addressed using the Markov chain model. Our efforts in this direction lead through a simplification of the mixing matrix incorporating both probabilities. We present the simplification and discuss some of its ramifications. We expect that it may lead to some improvement of the computational properties of the Markov chain model of the simple genetic algorithm