智能交通系统中的运营车辆优化调度研究

Optimizing Dispatching of Public Traffic Vehicles in Intelligent Transport Systems

阐述了遗传算法GA(GeneticAlgorithm)和禁忌搜索法TS(TabuSearch)的基本原理 ,有机结合两者优点 ,构成混合遗传算法HGA(HybridGeneticAlgo rithm) .针对公交车辆调度现状及所处的运营环境 ,运用HGA的智能化特征 ,进行了公交车辆智能调度研究 .仿真表明 ,基于GA TS的混合遗传算法优化公交车辆运营调度 ,能够有效地改善原有公交车辆运营调度的不足 ,提高动态运营决策效率和服务质量 .与常规方法相比 ,运行效率提高 1 5 % ,时间缩短 5 % ,这为公交车辆智能化运营调度提供合理、可行的调度手段 .

The basic principles of Genetic Algorithm (GA) and Tabu Search(TS) were expatiated on. Both of optimizing algorithms were availably integrated into Hybrid Genetic Algorithm (HGA). With regard to actual status and operation environment of Public Traffic Vehicles (PTV), intelligent dispatching of PTV was studied with HGA. The simulation results were demonstrated that intelligent dispatching of PTV could be realized to decision making, and the shortcoming could be effectively overcome based on GA TS Hybrid Genetic Algorithm. As a conclusion, the efficiency is 15% higher and traffic operation cycle 5% shorter than those of common PTV. In the way operation efficiency, traveling safety and service level of PTV were enhanced, the reasonable and viable means were provided for intelligent dispatching of urban PTV.