摘要
对LBS动态目标查找的研究,是为用户提供最短路径。通过对基础人工势场法进行改进,提出一种改进式人工势场法,构造出虚拟的引力场和斥力场,生成用户避障和移动的综合信息,同时将与蚁群算法相结合,从而寻找用户至目标的最短路线。改进算法有效的将改进式人工势场法和蚁群算法紧密结合在一起,通过对比,提高了普通蚁群算法的收敛速度。仿真证明所提算法在LBS最短路径应用中的有效性,同时该算法与传统蚁群算法相对比,证明算法有效的提高了搜索效率。
The dynamic target of LBS was studied in this paper. The paper improved the basis potential field method, and proposed an improved artificial potential field method. The algorithm uses the method to construct gravitational field and repulsive force field to generate the comprehensive information of obstacle avoiding and moving, and at the same time, utilizes ant colony algorithm to look for the shortest route for users. The algorithm combines artifi- cial potential field method with the ant colony algorithm closely and effectively, and improves the traditional ant colo- ny algorithm convergence speed. Simulation results show that the proposed algorithm is very effective in the shortest path of LBS application. While compared with traditional ant colony algorithm, the algorithm improves the searching efficiency of the algorithm.
出处
《计算机仿真》
CSCD
北大核心
2013年第5期349-353,共5页
Computer Simulation
关键词
改进式人工势场
蚁群算法
最短路径
Improved potential field
Ant colony algorithm
Shortest path
