To solve the problems of traditional structural optimization methods being prone to local optima, long computation time, and high memory consumption when dealing with high-dimensional nonlinear problems, a wind-resistant optimization design method for super high-rise intelligent buildings grounded on an improved genetic algorithm is proposed by studying the improvement of genetic algorithm through penalty function method. The findings indicate that this method can enhance the natural frequencies of the 1st and 2nd order structures, with amplification rates of 6.90% and 8.64%, respectively. After optimizing the design, the total values of transverse and downwind base shear forces are reduced by 3.60% and 1.21%, respectively. The total weight of the structure decreases from 52500 tons to 49830 tons, a decrease of 5.09%. Moreover, the research method has been demonstrated to outperform alternative approaches in terms of fitness convergence, solution stability, and constraint handling ability. The average optimization time, average objective function value, and fitness standard deviation of the research method are 1232s, 9.23×106, and 0.016×106, respectively. From this, the research method can enhance the lateral stiffness and response balance of the structure, verifying the engineering applicability and practical value of the proposed method in wind-induced response control of the structure.
