关键词: 鱼鹰优化算法, 高空翱翔勘探, 平衡能量因子, 工程优化问题, 路径规划

Abstract: Aiming at the defects of osprey optimization algorithm, such as weak global search ability, unbalanced exploration and exploitation, and easy to fall into local optimum, a hybrid strategy improved osprey optimization algorithm is proposed. A high-altitude flying exploration strategy is designed for the behavior of the osprey after the failure of fishing, which improves the global search ability of the algorithm, and then enhances the ability of the algorithm to get rid of the local extremum. An adaptive balance energy factor is introduced in the exploitation stage of the algorithm to balance the exploration and exploitation of the algorithm. In order to verify the performance of the proposed algorithm, it is experimentally compared with seven optimization algorithms on the CEC2017 test set, CEC2019 test set and CEC2022 test set, and the Wilcoxon rank sum test and Friedman test are performed on the experimental results. The experimental results show that the proposed algorithm has better optimization accuracy, convergence speed, and robustness. The effectiveness and practicality of the proposed algorithm are further verified by simulation experiments on 12 real-world engineering constrained optimization problems and robot path planning problems.

Key words: osprey optimization algorithm, high-altitude flying exploration, balance energy factor, engineering optimization problems, path planning