Novel hybrid response surface optimization method
一种新颖的混合响应面优化方法

This paper presented a novel method, called hybrid response surface optimization(HRSO) to reduce the number of evaluations in the process of optimization of black-box functions. The proposed method used hybrid response surface to build high accuracy black-box approximate models as surrogate-models. Then it updated the approximate model by circles of iteration. This paper applied the method on the Dixon-Szego test functions and estimated the performance by the number of function evaluations, when a run satisfied the convergence criteria. The results indicate that HRSO meets the same convergence by less evaluation comparing to Gutmann-RBF and CORS-RBF. And it can converge to global optimum quickly. It is a suitable method for solving expensive black-box problem.