Estimation of distribution algorithm using variety of information
Juan Yu, Yuyao He · 2014
Former information of probability model and inferior individuals were discarded in the research of estimation of distribution algorithm usually, but they may contain useful information. In this paper, the former probability information is introduced to avoid premature convergence caused by continuously select superior individuals of current population tobuilt probability model , and the individual sampling from superior probability model is filtered by inferior probability model to avoid generating inferior individuals. The algorithm is simulated through the widely used knapsack examples, the results verify the validity of the proposed method,and give suggestion for the choice of parameter through simulation and analysis.