多策略蚁群算法求解诱导维修路径规划
发布时间：2019-05-10 12:26
【摘要】：在诱导维修过程中,为了帮助维修者快速找到维修对象,提供高效安全的行走路径,需要对复杂的维修环境进行路径规划。传统的蚁群算法收敛速度慢、易陷入局部最优。为了提高寻优效率,对基本蚁群算法进行改进。提出了对α、β的自适应调整,改变信息素增量的更新方式,以及引入双向搜索策略,有效地提高了算法的收敛速度和全局搜索能力。仿真结果表明,改进的蚁群算法效率高,收敛速度快,能够为处在复杂维修环境中的维修人员提供高效的行进路线。
[Abstract]:In the process of induced maintenance, in order to help the repairman find the maintenance object quickly and provide an efficient and safe walking path, it is necessary to carry out path planning for the complex maintenance environment. The traditional ant colony algorithm converges slowly and is easy to fall into local optimization. In order to improve the efficiency of optimization, the basic ant colony algorithm is improved. The adaptive adjustment of 伪, 尾, the updating mode of pheromone increment and the introduction of bidirectional search strategy are proposed, which effectively improve the convergence speed and global search ability of the algorithm. The simulation results show that the improved ant colony algorithm has high efficiency and fast convergence speed, and can provide an efficient route for maintenance personnel in complex maintenance environment.
【作者单位】： 空军工程大学防空反导学院;
【基金】：国家自然科学基金资助项目(51405505)
【分类号】：E92;TP18
[Abstract]:In the process of induced maintenance, in order to help the repairman find the maintenance object quickly and provide an efficient and safe walking path, it is necessary to carry out path planning for the complex maintenance environment. The traditional ant colony algorithm converges slowly and is easy to fall into local optimization. In order to improve the efficiency of optimization, the basic ant colony algorithm is improved. The adaptive adjustment of 伪, 尾, the updating mode of pheromone increment and the introduction of bidirectional search strategy are proposed, which effectively improve the convergence speed and global search ability of the algorithm. The simulation results show that the improved ant colony algorithm has high efficiency and fast convergence speed, and can provide an efficient route for maintenance personnel in complex maintenance environment.
【作者单位】： 空军工程大学防空反导学院;
【基金】：国家自然科学基金资助项目(51405505)
【分类号】：E92;TP18
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