基于蚁群算法的智能交通最优路径研究  

The Research on the Optimal Path of Intelligent Transportation Based on Ant Colony Algorithm

作　　者：李松江[1] 张异[1] 龚跃[1] 

机构地区：[1]长春理工大学计算机科学技术学院,长春130022

出　　处：《长春理工大学学报（自然科学版）》2015年第4期122-126,共5页Journal of Changchun University of Science and Technology(Natural Science Edition)

摘　　要：针对车辆智能交通最优路径问题,提出一种实时规划的蚁群算法。在该算法搜索过程中加入针对具体问题的局部搜索寻优算法,在启发函数中引入搜索方向,改进信息素更新策略,限制信息素轨迹量。利用智能交通道路模型对改进算法进行比较分析。实验结果表明,改进后的蚁群算法能够有效地解决车辆实时路径诱导问题,实现车辆实时路径诱导,具有良好的收敛性和寻优性。Aiming at the intelligent traffic optimal path into local optimum problem proposed an improved ant process of join to solve the concrete problems of local ant colony algorithm convergence speed is slow and easy to fall colony algorithm, in the ant colony algorithm to search in the search optimization algorithm. In the heuristic function introduced search party to improved pheromone update strategy, limiting pheromone quantity, the state transfer rules introducing a priori knowledge, make ant colony tendency to have high adaptive value of search space, reduce the ant colony algorithm in blind search path into local optimum and shorten the search time. The experimental results show that the improved ant colony algorithm has good convergence and optimization, and can effectively avoid the stagnation of the algorithm in the local optimal solution, which proved the effectiveness of the improved algorithm.

关 键 词：蚁群算法 智能交通 最优路径 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]