摘要
基于交通网中交通流参数关系模型,提出了新的状态转移概率计算公式,同时在信息素更新策略中引入交通流密度因子,使算法可以根据时变的路网信息求解车辆的最短路径;利用蚁群算法和遗传算法相结合的思想来避免基本蚁群算法在求解车辆最短路径时易陷入局部最优解的缺陷。实验仿真结果表明,改进后的蚁群算法较基本蚁群算法能准确快速地找到基于时间的最短路径,并能有效解决实际交通系统中的最短路径问题,具有一定的实际意义和参考价值。
Based on the model of the traffic parameters,a new computing formula of the transition probability is proposed.And traffic density factor is introduced in pheromone update strategy,and as a result,the algorithm could resolve the shortest path problem with the real-time trafic information.To avoid the algorithm converging to the local optimal result,the ant colony algorithm was combined with genetic algorithm.The results of the experimentation prove that the improved algorithm could find the shortest path more accurately and quickly than the basic algorithm.Besides this,the improved algorithm can resolve the shortest path problem of traffic system of reference value and actual meaning.
出处
《常州大学学报（自然科学版）》
CAS
2012年第1期78-81,共4页
Journal of Changzhou University：Natural Science Edition
关键词
蚁群算法
最短路径问题
实时交通信息
ant colony algorithm
shortest path problem
real-time traffic information
