Study on Train Operation Adjustment based on Hybrid Convergent Particle Swarm Optimization
Train operation adjustment is an important part of the railway dispatch work, which is the core work to assure the transportation order and efficiency. The essence of the adjustment is to adjust the train to run according to the planned schedule. In this paper, a train operation adjustment model is built and the hybrid convergent particle swarm optimization is employed to solve the optimizing problem. It not only satisfies the constraints of train operation adjustment, bt also has the real-time adjusting ability. Computing results are changed into a train operation adjustment plan. It is concluded that the algorithm has excellent performance, compared with the basic swarm algorithm. The train operation adjustment plan is practical and efficient.
hybrid convergent particle swarm optimization train operation adjustment
MENG Xuelei JIA Limin QIN Yong XU Jie ZHOU Tao
State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing, China T State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing, China
国际会议
张家界
英文
326-329
2009-04-11（万方平台首次上网日期，不代表论文的发表时间）