Aeroelastic structure optimization technique mainly consists of two aspects: constraint solving and optimization algorithms. Aiming at the high efficiency but low accuracy of static aeroelasticity analysis method based on lowerorder panel method, a high precision static aeroelasticity analysis method based on highorder panel method is established. Aiming at the characteristics of the current aeroelastic structure optimization technology that the single optimization algorithm results in low search accuracy and slow convergence speed, a genetic/fractal hybrid algorithm is developed by combining genetic algorithm and fractal algorithm. Aiming at the characteristics of long computational time and high device requirement of static aeroelasticity structure optimization, the Kriging surrogate model is introduced to speed up optimization and reduce the time and device cost. Finally, taking a large aspect ratio aircraft wing as an example, the static aeroelastic analysis method based on higherorder panel method is used to solve the constrained response samples, and the Kriging surrogate model method is used to construct and predict the constraint response. Combined the Kriging surrogate model with the genetic/fractal hybrid optimization algorithm, a highefficiency and highprecision static aeroelastic structure optimization method is built. The result of optimization analysis shows that the Kriging surrogate model has high precision in predicting the static aeroelastic response with the average error below 5%, and the average error of the aileron efficiency forecast even below 1%. Compared to the single genetic algorithm, the genetic/fractal hybrid algorithm has faster convergence speed and stronger global optimization ability.