基于改进蚁群算法的动态多路径诱导系统研究  

Study on Improved Ant Colony Algorithm in Dynamic Multi-paths Route Guidance System

作　　者：董永峰[1] 刘艳柳[1] 张娜[1] 顾军华[1] 

机构地区：[1]河北工业大学计算机科学与软件学院,天津300401

出　　处：《河北工业大学学报》2010年第3期46-50,55,共6页Journal of Hebei University of Technology

基　　金：河北省科技计划项目(09213507D)

摘　　要：传统的动态路径诱导系统只能向出行者提供唯一一条最优路径,可能引起出行者的集聚反应,进而导致拥挤漂移问题的出现.本文提出了一种基于改进蚁群算法求解最短路径的方法,实现了动态路径诱导系统中最短路径的搜索.改进蚁群算法对信息素和启发信息进行标准化,消除量纲和取值范围的影响,引入方向函数作为新的启发式因子,使算法的收敛速度得到提高.仿真实验表明该方法收敛速度比较快,搜索结果比较合理、有效,能够满足动态路径诱导的实时性和快速性要求.The traditional Dynamic Route Guidance System （DRGS） provides only the optimal path to the travelers which may easily lead to aggregative response ofthe travelers finally may result in overcrowding drift. This paper presents an approach based on Ant Colony Optimization （ACO） for solving the k-shortest paths problem in DRGS. In order to improve the convergence rate, the basic ACO is improved by introducing direction function the weight coefficient of which can be adjusted to vary state transition rule and standardized transformation to eliminate the influence of the size and dimension of pheromone and heuristic information. Compared with basic ACO, simulation experiments indicate that the improved ACO is more effective and efficient.

关 键 词：蚁群算法 动态诱导系统 方向函数 多路径诱导 

分 类 号：TP394.5[自动化与计算机技术—计算机应用技术]