A fast global optimizer based on improved CS-RBF and stochastic optimal algorithm

An improved compactly supported radial basis function is proposed as a response surface model in the study of computationally heavy design problems. A new interpolation formula is introduced to enhance the interpolation accuracy on boundary derivatives and the proposed response surface model is then combined with stochastic algorithms in the design of a fast global optimizer. Numerical results are reported to demonstrate the generality and the robustness of the proposed works.