基于大数据蚁群择优算法的飞机航行最优路径规划研究  

Research on Optimal Path Planning Based on Big Data Ant Selection Algorithm

作　　者：刘娇 LIU Jiao(School of statistics,University of International Business and Economics,Bbeijing 100029 China)

机构地区：[1]对外经济贸易大学统计学院,北京100029

出　　处：《长江信息通信》2025年第2期37-39,共3页Changjiang Information & Communications

摘　　要：为了降低飞机执行任务阶段的航行距离,对路径进行合理规划是极为必要的,为此,提出基于大数据蚁群择优算法的飞机航行最优路径规划研究。引入预定义边界优先的点线化处理方法确定飞机任务区域范围,利用一维轨迹对应n阶多项式确定具体的规划策略后,利用大数据蚁群算法对飞机一维轨迹n阶多项式的参数最优值进行求解,并设置具体的状态转移概率和信息素更新策略。In order to reduce the navigation distance of the mission stage,it is extremely necessary to plan the path reasonably.Therefore,the optimal path planning study based on big data ant colony selection algorithm is proposed.Introduce predefined boundary first point linear processing method to determine the aircraft mission area,using the one-dimensional trajectory corresponding to n order polynomial to determine the specific planning strategy,using the large data swarm algorithm for the optimal value of aircraft trajectory n order polynomial parameters,and set up the specific state transition probability and pheromone update strategy.

关 键 词：大数据蚁群择优算法 飞机航行 最优路径规划 预定义边界优先 点线化处理 一维轨迹n阶多项式 状态转移概率 信息素更新策略 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]