数字化城市交通向导仿真的蚁群优化算法

以求解旅行商问题的蚁群算法为基础,充分考虑交通向导最佳路径的具体要求,对算法的选择机制、更新机制以及协调机制作进一步改进,引入自适应的转移策略,并融入节约法,以克服基本蚁群算法计算时间长、易出现停滞等缺陷。以湖北荆门地区车辆选择路径为研究对象,采用蚁群优化算法建立了车辆最佳路径的模型,并对其进行了仿真分析。仿真实验结果表明,优化算法比基本蚁群算法的路径更优,寻路时间更短。

Method for Digital Simulation of Urban Traffic Wizard with Optimized ant Colony Algorithm

This paper introduces a new method about digital simulation of urban traffic .Based on the ant colony algorithm for solving TSP （ traveling salesman problem ） ,the best path fully considered traffic guid-ance specific requirements of the algorithm selection mechanism ,the update mechanism and coordination mechanisms for further improvement ,introducing adaptive shift strategy ,and integration into the conserva-tion Act,in order to overcome the problems of basic ant colony algorithm：wasting of time,prone to stagna-tion and other defects .This paper vehicle choose paths in hubei jingmen city as the research object ,the ant colony optimization algorithm is adopted to establish the best route model of vehicles .And we there-fore based on simulation results comparing with the basic algorithm results and concluded that the result is shorter.