摘要
无人飞行器航迹规划是现代战争中实施远程精确打击,提高飞行器实际作战效能的关键技术。蚁群算法作为一种启发式仿生优化算法,能够有效应用于航迹规划中。针对基本蚁群算法在应用中容易过早陷入局部最优解这一缺点,提出自适应动态双种群蚁群算法的改进策略,通过信息素的震荡变化和挥发系数的自适应调整,扩大搜索空间,提高算法搜索的全局性。并将改进后的算法应用于无人飞行器航迹规划,通过实验仿真,证明了此改进算法在航迹规划应用中的可行性和有效性。
Route planning of UAV is an important technique in long-range precision strikes and improve the combat effectiveness of aircraft.Ant colony algorithm as a heuristic bionic optimization algorithm can be effectively applied to route planning.The prominent shortcoming of the basic ant colony algorithm is easily trapped into local optimal solution.Adaptive dynamic dual population ant colony algorithm is proposed in this paper in order to solve this problem.The concussion change of the pheromone and the adaptive adjustments of the volatile coefficient can expand the search space and improve the overall searching performance.It is proved that the algorithm is feasible and effective in the route planning simulation.
出处
《计算机与数字工程》
2010年第7期41-44,146,共5页
Computer & Digital Engineering
关键词
航迹规划
蚁群算法
自适应
信息素
route planning
ant colony algorithm
adaptive
pheromone
