Taking account of that it is difficult to obtain the error function to make sequential re-sampling optimization when the predicted error of sampling points in radial basis function(RBF) interpolation surrogate model is zero, the constraint of sampling point distribution was applied in the process of sequential re-sampling. Taking advantage of the convergence performance of potential optimal solution, a re-sampling strategy which is suitable for the sequential optimization of RBF interpolation surrogate model was proposed. The strategy matches the input response property of emulation model with the spatial distribution property of sampling points. Simulation results indicate that the optimization efficiency and precision of the proposed strategy is higher than that of the traditional optimization method based on surrogate model. The optimum point can be well predicted and the number of computational times in primitive model can be reduced obviously by the proposed strategy.