基于改进蚁群系统的动态交通分配

现有动态交通分配模型大多使用数值算法求解,无法保证分配结果的准确性。蚁群算法作为一种分布并行计算的启发式算法,能够高效求解网络分配问题,但是,现有算法虽然保证了局部搜索效率,却忽略了全局搜索能力和对出行状况变化的动态反馈。本文在算法中插入阻抗计算步骤,将每步蚂蚁择路结果通过计算生成决策因子,并据此自适应调整算法参数,模拟实际出行者易于得到实时路况信息而有趋向性的择路行为,在保证局部搜索效率的前提下,增加算法求解质量和全局搜索能力。最后,分别使用改进前后的算法求解模型进行对比。结果表明,改进算法的分配结果更优,且路网流量分配更均衡,离散程度小,路网利用率高。改进算法求解模型具有理论结合实际的优势。

Dynamic Traffic Assignment Based on Improved Ant System

Most of the existing dynamic traffic assignment models are solved by numerical algorithms,which can not guarantee the accuracy of the assignment results.As a heuristic algorithm for distributed parallel computing,ant colony algorithm can efficiently solve the network assignment problem.However,the existing algorithm,while guaranteeing the efficiency of local search,ignores the global searching ability and dynamic feedback to the changes of travel conditions.In this paper,the impedance calculation step is inserted into the algorithm,and the ant routing result is computed to generate the decision factor,and the algorithm parameters are adaptively adjusted to simulate the actual traveler's taxis routing behavior which is easy to obtain real-time road condition information,and increase the quality and global searching ability of the algorithm under the premise of guaranteeing the local search efficiency.Finally,the improved and the original algorithm are used to solve the model.The results show that the improved algorithm has better assignment results,more balanced traffic distribution,less discrete degree,and high utilization of road network.The improved algorithm has the advantage of combining theory with practice.