Multi-UAV Path Planning based on Improved Harris Hawk Optimization Algorithm

This paper addresses the multi-UAV path planning problem by proposing an improved Harris Hawks Optimization algorithm （IHHO）. The algorithm designs a multi-UAV collaboration strategy based on the Separation-Alignment-Cohesion （SAC） principle, coordinating UAV movements through precise velocity control formulas to ensure group safety and coordination. To further enhance performance, an adaptive nonlinear energy regulation mechanism is introduced to optimize the balance between global and local search, while a progressive adaptive focusing strategy dynamically adjusts the search process. Additionally, the integration of random jumping and distribution optimization strategies enhances the ability to escape local optima. Through validation using international standard test functions and comparative experiments in UAV path planning, the results demonstrate that IHHO significantly outperforms the traditional HHO algorithm in terms of solution accuracy, convergence speed, robustness, and avoidance of local optima.