摘要
研究交通道路中的最短路径优化问题,由于城市道路拥塞严重,在导航过程中,为了尽快达到目的地,必须选择最短路径进行行驶。传统搜索算法计算复杂度高,寻优效率低,不利于实际优化。为解决最短路径优化问题,提出了一种蚁群算法的GIS中的最短路径优化方法。将路径的起点当成蚁群的巢,终点当成蚁群要寻找的食物,蚂蚁通过信息法指导搜索方向,并通过蚂蚁之间的相互协作达到终点。仿真结果表明,提出的优化方法降低了计算复杂度,更快地找到最短路径,提高了找到最短路径的平均正确率,为解决GIS中的最短路径优化问题提供了一种新的有效途径。
In navigation process,in order to save costs and reach the destination as soon as possible,we must choose the shortest path.Modern city traffic networks are complex,and the traditional search algorithm with high computational complexity and low searching efficiency,is not conducive to the practical application.In order to solve the problem of shortest path of GIS,we put forward a kind of ant colony optimization and the shortest path in GIS as an optimization method.The path starting point as the ant nest,and the finish point as ant colony to find food.The ants search the direction based on information method,and reach the destination through the mutual cooperation among the them.The simulation results show that the proposed optimization method can reduce the computational complexity,and find the shortest path quickly,and improve average correct rate of the shortest path.
出处
《计算机仿真》
CSCD
北大核心
2011年第12期357-360,397,共5页
Computer Simulation
基金
安徽省教育厅质量工程项目(20101985)
关键词
最短路径
蚁群算法
信息素
地理信息系统
Shortest path
Ant colony algorithm
Pheromone
Geographical information system（GIS）
