  In this paper, we obtain bounds on the probability of convergence to the
optimal solution for the compact Genetic Algorithm (cGA) and the Population
Based Incremental Learning (PBIL). We also give a sufficient condition for
convergence of these algorithms to the optimal solution and compute a range of
possible values of the parameters of these algorithms for which they converge
to the optimal solution with a confidence level.
