基于一种改进粒子群算法的水下远程武器航路规划

摘要

An improved particle swarm optimization (PSO) algorithm with particle exchanging is proposed to solve the problem of moving back in the route planning of underwater long-range weapon based on basic PSO. Combining the route planning model of the underwater long-range weapon, this improved PSO algorithm is used in a combat simulation system of a certain long-range weapon. Simulation result shows that this algorithm can enhance the effect of the route planning and be helpful to the operational application of the long-range weapon.%针对水下远程武器航路规划中,采用基本粒子群算法避障出现的航路倒退问题,提出了一种借鉴遗传算法采用粒子对换的改进粒子群优化(PSO)算法,并结合远程武器的航路规划设计模型,应用于水下武器作战仿真系统.计算结果表明,该算法可有效提高远程武器航路规划避障的计算效果,对水下远程武器的作战使用研究具有一定的参考价值.