论文部分内容阅读
针对蚁群算法在航迹规划中易于过早陷入局部最优解这一问题,提出了一种双向自适应改进蚁群算法。使用栅格节点对飞行空间进行建模,在搜索过程中以移动方向一定范围内最大信息素和目标引导函数作为启发因子。根据蚁群算法处理该问题时的信息素散播特点,重构了信息素的更新策略和散播方式。通过信息素的震荡变化和挥发系数的自适应调整,扩大了搜索空间,提高了搜索全局性,获得了一种有效的航迹规划算法,并取得了较好的仿真结果。
Aiming at the problem that ant colony algorithm tends to fall prematurely into the local optimal solution in the trajectory planning, a two-way adaptive improved ant colony algorithm is proposed. Grid nodes are used to model the flight space. During the search process, the maximum pheromone and the target guidance function within a certain range of moving direction are taken as the heuristic factors. According to the characteristic of pheromone propagation when the ant colony algorithm deals with this problem, the pheromone updating strategy and the dissemination mode are reconstructed. Through the adjustment of pheromone oscillation and the adaptive adjustment of volatility coefficient, the search space is expanded and the overall search is improved. An effective algorithm of track planning is obtained and a good simulation result is obtained.