粒子群优化算法在舰船路径优化仿真中的应用

Application of particle swarm optimization algorithm in ship path optimization simulation

为保障舰船安全稳定航行,显著提升舰船续航能力,设计了基于粒子群算法的舰船路径优化方法。使用概率图法构建舰船航行路线图,按舰船在航行性能方面的评价指标,构建与舰船航行路线图相关、综合考虑舰船转弯角度以及地形威胁等约束的舰船航行路径优化模型,并应用改进粒子群算法求解所构模型,得到满足约束条件的舰船航行初始最优路径。之后通过删除冗余点的方式对舰船航行初始最优路径实施平滑优化处理,得到最终的舰船航行最优路径。实验结果表明,该方法可收获更优的舰船航行路径,舰船按该路径行驶,更有利于续航,使舰船航行任务得以有效完成。

To ensure the safe and stable navigation of ships and significantly improve their endurance,a ship path optimization method based on particle swarm optimization algorithm has been designed,.Using probability graph method to construct a ship navigation route map,based on the evaluation indicators of ship navigation performance,a ship navigation path optimization model is constructed that is related to the ship navigation route map and comprehensively considers constraints such as ship turning angle and terrain threat.The improved particle swarm optimization method is applied to solve the constructed model,and the initial optimal path of ship navigation that meets the constraint conditions is obtained,Afterwards,the initial optimal path for ship navigation is smoothed and optimized by deleting redundant points to obtain the final optimal path for ship navigation.The experimental results show that this method can obtain better ship navigation paths,and the ship follows this path,which is more conducive to endurance and enables the ship to complete navigation tasks effectively.