A new sample update strategy based on kringing

The study presented in this paper sets up a new mixing sample update strategy based on the Kriging model to address the issue of accuracy in complicated engineering optimization problems by adding points dynamically. First, a new optimized Latin Hypercube Sampling experiment design method is established to increase the homogeneity of the sample. Second, a sample update strategy based on local optimization and EI-based Kriging model is established. Three numerical samples are carried out to compare the results of traditional popular method EGO, and the results show that this method has increased the accuracy and the efficiency. The successful application of this method on RAE2822 Airfoil using less sample and reducing 14.3% of the drag has further proven the effectiveness of this method.