Aimed at solving the problem of optimization convergence and the global optimization, this research proposes a Combined Optimization Methodology, which combines the global and local optimization methods. The former one can obtain global optimum solution but converge slowly, while the latter one can converge fast and obtain a local optimum solution and can be sensitive to initial value. Firstly, the approximation function of the original problem was built. Then the approximate optimum solution was obtained by the global optimization method. The approximate optimum was taken as the initial value, and the real optimum solution is obtained by the local method optimizing the original problem directly. In order to achieve better approximation, the RBF was improved and Shape Parameter Optimization Radius Basis Function was developed by using the surrogate model. Both of the methods were used in the near space aircraft wing optimization. Results show that the modified interpolation method is more accurate than the Kriging model, and the Combined Optimization can obtain the optimum and improve the convergence speed.