智能交通系统中车辆调度问题的遗传算法研究

在智能交通系统(ITS, Intellignet Transportation Systems)的各个子系统中,先进的公共交通系统(APTS, Advanced Public Transportation System)具有重要地位和作用,其中车辆调度问题是APTS的关键.为了提高车辆调度的智能化,提出了一种基于遗传算法(GA, Genetic Algorithm)的公交车辆智能调度方法,采用最小费用作为目标函数,考虑了车辆配置、时间、运营效率及资源利用等方面因素,通过选择、交叉及变异等遗传操作,得到了最优的调度排序方案,并对2种交叉方式进行了比较,仿真结果表明,利用GA解决车辆调度问题具有可行性、先进性和快速性. 

Genetic Algorithm for the Scheduling of Public Traffic Vehicles in ITS

Advanced Public Transportation System(APTS) is very important for the development of the subsystems of an Intelligent Transportation System (ITS). Vehicle Scheduling is a key technology of APTS. To improve the intelligence of vehicle scheduling, a new Genetic Algorithm(GA) based method for intelligent scheduling of public vehicle is proposed, with the minimum cost as the objective function. Factors explicitly considered in this paper include vehicle assignments, timing, operating efficiency and resource usage. An optimal scheduling scheme is produced by using genetic operator including selection, crossover and mutation. At the same time, two kinds of crossover are compared. Simulation result shows that the GA based method for vehicle scheduling is feasible, advanced and efficient.