多策略蚁群算法求解诱导维修路径规划  

Route Planning of Induced Maintenance Based on Improved ant Colony Algorithm

作　　者：饶楚锋 韩华亭[1] 瞿珏[1] 王崴[1] 彭勃宇 

机构地区：[1]空军工程大学防空反导学院,西安710051

出　　处：《火力与指挥控制》2017年第10期82-86,共5页Fire Control & Command Control

基　　金：国家自然科学基金资助项目(51405505)

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。In the process of inducing maintenance,in order to help the maintenance person to findthe maintenance of the image quickly,and to provide a safe and efficient way to walk,there is a needto make a maintenance path planning for its complex maintenance environment. The traditional antcolony algorithm is slow convergence and easy to fall into local optimum. In order to improve theoptimization efficiency,the basic ant colony algorithm is improved. The adaptive adjustment of α、β,pheromone increment adjustment factor and the bidirectional search strategy are introduced to improvethe basic ant colony algorithm,which improve the solution effciency of the algorithm greatly. Thesimulation results shows that the improved ant colony algorithm has high efficiency and fastconvergence speed and is able to provide efficient route for the maintenance personnel in complexmaintenance environment.

关 键 词：诱导维修 路径规划 蚁群算法 自适应 双向搜索 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]