Objective Aiming at the problems of low optimization accuracy and easy fall into local optimization of the Bald Eagle Search BES in function optimization a Hybrid Strategy Improved Bald Eagle Search HSIBES was proposed. Methods First the Logistic mapping strategy was used to initialize the population to make the population distribution more uniform. Secondly Levy flight was introduced in the search space stage the step size was controlled the convergence effect was improved and the local optimal was jumped. Finally the adaptive inertial weight was used in the search for space food to improve the convergence speed and accuracy and to balance the local and global search capabilities of the algorithm. Results The HSIBES algorithm was compared with other five benchmark algorithms and other improved algorithms by other scholars and the performance of the HSIBES algorithm was verified by simulation experiments on 9 test functions and Wilcoxon rank sum test and it was found that the results of HSIBES were better than other comparison algorithms and there was a significant difference between them and other comparison algorithms. Conclusion The experimental results show that the HSIBES algorithm has better optimization accuracy convergence speed and stability and the performance of the algorithm is superior.