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《Journal of Beijing University of Aeronautics and Astronautics》 2003-01
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Genetic Algorithm for the Scheduling of PublicTraffic Vehicles in ITS

Teng Jitao (School of Automation Science and Electrical Engineering, Beijing University of Aeronautics and Astronautics) Zhang Feizhou (Peking University, Institute of Remote Sensing and Geography Information System) Li Yaopeng Fan Yuezu (School of Automation Science and Electrical Engineering, Beijing University of Aeronautics and Astronautics)  
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.
【Fund】: 国家高技术 863计划资助项目 (863 3 0 6 ZT0 4 0 3 4)
【CateGory Index】: U491
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