An improved whale optimization algorithm based on siege mechanism is proposed to solve the problems of the traditional whale optimization algorithm, such as its insufficient global exploration ability, low convergence accuracy and slow speed. Firstly, the algorithm uses Tent chaos mapping and nonlinear parameters to make the population distribution more uniform and coordinate the exploration and development ability of whale optimization algorithm. Then, considering the important role of algorithm fitness in optimization, the limited fitness control and Gaussian detection mechanism are proposed. Finally, combined with the siege mechanism of the Harris hawks optimization algorithm, the global exploration and local optimization capabilities of the whale optimization algorithm are improved. The results show that the improved whale optimization algorithm based on the siege mechanism has good robustness and stability, while ensuring the convergence accuracy and speed.