A further result on the Markov chain model of genetic algorithmsand its application to a simulated annealing-like strategy

摘要

This paper shows a theoretical property on the Markov chain ofngenetic algorithms: the stationary distribution focuses on the uniformnpopulation with the optimal solution as mutation and crossovernprobabilities go to zero and some selective pressure defined in thisnpaper goes to infinity. Moreover, as a result, a sufficient conditionnfor ergodicity is derived when a simulated annealing-like strategy isnconsidered. Additionally, the uniform crossover counterpart of thenVose-Liepins formula is derived using the Markov chain model