摘要
求解交通路网中两点间的最短路径是智能交通系统中的一个重要功能,为了更为准确快速地找到最优解,这里分析Dijkstra算法处理动态车辆路径问题中的缺陷,提出一种改进的蚁群算法,即在基本蚁群算法中引入搜索方向和搜索热区机制提高算法的搜索性能。通过建立改进蚁群算法模型,用VC 6.0开发工具,以实际交通地图为例,求解交通网络两点间最短距离;并与基本蚁群算法进行对比。仿真实验表明,传统蚁群算法的平均迭代次数为71.06,改进蚁群算法平均迭代次数为55.82,比传统蚁群算法有了明显的提高。该方法能有效解决交通系统最短路径问题,具有一定的实际意义和参考价值和实际意义。
Searching shortest path of the transportation network is one of the most important functions of ITS,in order to find the optimization path accurately and rapidly,disadvantages of using Dijkstra algorithm to deal with dynamic shortest path and a kind of modified ant colony algorithm are analysed and proposed,in which the mechanism of search direction and search hot section are introduced to improve searching performance. Through building modified ant colony algorithm model, using VC6.0 developing tool, for a example with actual traffic map, resolving the shortest path of the transportation network and contrasting the ant colony algorithm. Simulated experiments show that：average iterative times using the ant colony algorithm is 71.06, average iterative times using the modified ant colony algorithm is 55.82, the latter improved obviously. The modified ant colony algorithm can resolve the shortest path problem of traffic system of reference value and actual meaning.
出处
《现代电子技术》
2009年第8期76-78,共3页
Modern Electronics Technique
关键词
蚁群算法
最短路径
信息素
智能交通系统
ant colony algorithm
shortest path
pheromone
intelligent traffic system
