On the mean convergence time for simple genetic algorithms

We describe genetic drift by a Markov model and give the mean convergence time under genetic drift in the context of GAs. Our analyses of GAs make use of the Markov chain formalism based on the Wright-Fisher model which is a typical model in genetics. The states of the Markov chain are given. Then, we consider the mean convergence time to the absorbing states of the Wright-Fisher model. Finally, we derive an optimal mutation rate for GAs and show that this rate works effectively