基于动态自适应蚁群算法的航线规划仿真  

Route Planning Simulation Based on Dynamic Adaptive Ant Colony Algorithm

作　　者：张欢[1] 吴军[1] 彭芳[1] 

机构地区：[1]空军工程大学航空航天工程学院,陕西西安710038

出　　处：《现代防御技术》2014年第5期139-144,153,共7页Modern Defence Technology

摘　　要：蚁群算法是一种新型的基于群体的仿生算法,其在解决飞机航线规划问题中已经获得了较为广泛的应用。在传统蚁群算法的基础上提出了一种动态自适应调整信息素蚁群算法的航线规划算法,即在航线点搜索过程中对信息素强度Q值进行动态自适应调整,并将三维地形、雷达威胁等因素结合到算法中。仿真结果表明,该改进算法能够有效解决扩大搜索空间和寻找最优解之间的矛盾,帮助飞行员更快地规划出一条最优航线,为更好完成作战任务奠定了良好的基础。The ant colony algorithm is a new bionic algorithm based on groups, and has been widely used in the aircraft route planning problem. Based on traditional ant colony algorithm, a new method u- sing dynamic adaptive adjusting pheromone of ant colony algorithm is proposed, namely, the pheromone intensity Q value is dynamically adaptively adjusted in the process of route planning search, and factors such as 3D terrain, radar threat will be combined into the algorithm. The simulation results show that the improved algorithm can effectively solve the contradiction between expanding the search space and search- ing for optimal solution, help pilots plan out an optimal route more quickly, and lays a good foundation for pilots complete the mission better.

关 键 词：蚁群算法 航线规划 信息素 自适应 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术] TJ765.2[自动化与计算机技术—计算机科学与技术]