Multi-Population Bayesian Optimization Algorithm using Cooperated Pattern Search Strategy

This paper proposed a multi-population based Bayesian optimization algorithm (BOA). It combines the Bayesian statistic optimization technique with multi-population scheme. And the cooperated pattern search mechanism is provided, which is used to avoid premature convergence problem. It includes the pattern selection, model structure update and model parameter update processes. And a constraint planning model is used to balance the parameter update process. The results of examination test show the new algorithm´s efficiency.