Why Are Clonal Selection Algorithms MCMC

Clonal selection algorithms are considered. Two algorithms are designed and executed to obtain purely empirical analysis conclusions in order to turn to purely theoretical analysis results about the behavior of clonal selection algorithms as Markov chains, which conflrm the conjectures from these experiments and in order to introduce a complete framework toward a new philosophy of MCMC method and of statistical inference method about Markov chains. First, we model clonal selection algorithms using Markov chains. Second, we carry on a particle analysis and analyze the convergence properties of these algorithms. Third, we propose the unifled MCMC theorem and unique chromosomes method for a purely successful optimization of these algorithms.