摘要
针对蚁群算法在水下无人航行器航路规划中出现的收敛效率低和易早熟收敛的问题,文章采用包含混沌算子的最优-最差信息素更新和变尺度混沌局部搜索的措施,提高算法全局寻优能力,最后通过仿真验证了改进算法的有效性。
In view of the low convergence efficiency and premature convergence of the ant colony algorithm in the route planning of the underwater unmanned vehicle,in order to avoid the algorithm from falling into the local optimal,the optimalworst pheromone update and change including the chaos operator are used.The measure of scale chaos local search improves the algorithm's global optimization ability.Finally,the effectiveness of the improved algorithm is verified by simulation.
作者
杨帆
李笑瑜
Yang Fan;Li Xiaoyu(Aeronautical Engineering Institute,Jiangsu Aviation Vocational and Technical College,JiangsuZhenjiang212134,China)
出处
《信息通信》
2020年第9期38-40,共3页
Information & Communications
基金
校级课题:多旋翼无人机编队飞行路径规划方法研究1
关键词
水下无人航行器
航路规划
混沌算子
仿真验证
Underwater unmanned aerial vehicle
Pathplanning
Chaosoperator
Simulation
