一种可用于AUV航路规划的改进粒子群优化算法

摘要

在差分进化算法(DE)和量子粒子群优化算法(QPSO)基础上,提出了一种改进量子粒子群优化算法,并将其成功地应用于海洋环境下的AUV航路规划.仿真实验结果表明,在不同的战场环境下(不同的发射点,不同的目标点,不同的侦测威胁),改进量子粒子群优化算法寻优能力强、收敛速度快、算法稳定性好,可较好地适应AUV航路规划.%Based on the differential evolution algorithm(DE)and quantum particle swarm optimization algorithm(QPSO), this paper proposes an improved quantum particle swarm optimization algorithm,which is successfully applied to AUV route planning in the marine environment.Simulation results show that in different battlefield environment(different launch points, different target points,different detection threats),the improved quantum particle swarm optimization algorithm has the ad-vantages of strong searching efficiency, fast convergence speed and good algorithm stability, which can be well adapted to AUV route planning.