摘要
文章针对现有大型停车场管理系统中存在的车位诱导问题,以停车路径最短作为最佳车位的确定准则,基于寻找空闲车位的分析过程,建立了停车场车位分布图背景下的最佳车位数学模型,且将该模型转化为最短路径问题,结合智能优化方法——蚁群算法形成车位诱导算法,对模型进行寻优,并给出了具体的求解步骤。最后结合一个实际的停车场背景进行仿真,确定最佳车位,为入场车辆的停放提供向导,解决车主寻找车位时的盲目性,并提高停车场管理系统的智能化程度。
Considering the parking guidance in the management systems of modern large - scale parking lots, the best parking space is chosen according to the shortest parking path. After analyzing the searching process from the entrance to unoccupied parking spaces, a math model to implement the best parking space based on the parking lots＇ map is built up, which is turned to a shortest path problem. Moreover, an intelligent optimal algorithm, that is, ant colony algorithm is used to get the optimum solution and the main steps are given. Finally the simulation with an actual parking lot is showed and the experimental result can solve the blindness of parking, help the parking guidance and the improvement of the management system.
出处
《计算机仿真》
CSCD
2007年第11期176-178,共3页
Computer Simulation
关键词
停车场
最佳车位
最短路径
蚁群算法
Parking lots
Best parking space
Shortest path
Ant colony algorithm
