Research on bayesian optimization algorithm selection strategy

Probability model accuracy is the base of Bayesian Optimization Algorithm and data sample is the base of construction accuracy model. So sample strategy is critical for the algorithm. In test, tournament selection,truncation selection and proportional selection are adapted to deal with typical dependency-free function, bivariate dependencies function and multivariate dependencies function. The result shows that tournament selection is the best selection strategy for Bayesian Optimization Algorithm, truncation selection and proportional selection are unsuitable for the algorithm.