Reference to the probability model of information transmission

a new estimation of distribution algorithm is proposed for non numerical optimization problems.Firstly

an updating model of a priori knowledge probability is built according to the superior information produced during evolution process

and the model of conditional transfer probability is also constructed based on the emerging frequencies of neighboring symbols.Secondly

the model of posterior probability is given by combining the above mentioned probability model to guide new population generating.Finally the presented approach is tested on TSP problems

and the results show that the proposed algorithm can improve the premature convergence of estimation of distribution algorithms.