摘要
针对巡航导弹航路规划问题,提出了一种竞争量子进化算法(CQEA),算法通过双方向进化及自适应变异避免其陷入局部最优解。同时,鉴于航路重规划对实时性的高度要求,借助最小威胁曲面及搜索竖线将三维搜索空间降到一维,并引入功能区域簇初始化思想来保证初始种群皆为非劣个体,从问题的几何本质上提升航路重规划效率。最后利用CQEA算法进行了航路规划与重规划仿真实验,结果表明,与PAQEA相比,CQEA搜索效率更高,稳定性更好;与原三维搜索空间相比,通过削减搜索空间及引入功能区域簇初始化思想后算法搜索速率更快,符合航路重规划对实时性的高度要求。
Aimed at the problem of cruise missile path planning, a Competition Quantum Evolutionary Algo- rithm （CQEA） is proposed in this paper. The algorithm is a kind of optimum solution through two direc- tion evolution and self-adapting variation to avoid to land itself into the local. Meanwhile, for the real-time request of path re-planning, surface of minimum risk and search vertical bar are reduced to decline the di- mension of the primary 3-dimensional space. The initial population is obtained through an idea of opera- tional area cluster to guarantee its non-inferiority. The simulation results show that compared to PAQEA, CQEA is good in searching efficiency. And compared to 3-dimensional space, CQEA is good in perform- ance in the new searching space.
出处
《空军工程大学学报（自然科学版）》
CSCD
北大核心
2016年第6期28-34,共7页
Journal of Air Force Engineering University(Natural Science Edition)
基金
国家自然科学基金(2014JQ8339)
关键词
巡航导弹
航路重规划
竞争量子进化算法
搜索竖线
最小威胁曲面
功能区域簇
cruise missile
path re-planning
competition quantum evolutionary algorithm
search vertical bar
surface of minimum risk
operational area cluster
