Optimization of Multi-group Train Operations for Transit Urban Rail with Even Load

被引：0
|
作者：
Rong Y.-P. [1 ]
机构：
[1] Transportation and Economics Research Institute, China Academy of Railway Sciences Corporation Limited, Beijing
来源：
Jiaotong Yunshu Xitong Gongcheng Yu Xinxi/Journal of Transportation Systems Engineering and Information Technology | 2019年 / 19卷 / 04期
关键词：
Bi-level programming model; Multi-group train; Nested genetic algorithm; Train operational schemes; Urban rail transit; Urban traffic;
D O I：
10.16097/j.cnki.1009-6744.2019.04.027
中图分类号：
U2 [铁路运输];
学科分类号：
摘要：
Multi-group train operations is one important part of the network operation technologies. In order to solve the problem that the train with fewer vehicles is over oversaturated and the train with more vehicles has a lower load factor, a bi-level programming model is established considering the equilibrium of load factor between different trains. The constraints are policy headway, platform length, maximum load and fleet size. The upper-level model is an optimization model of train plan, which is used to determine the optimal frequencies of two types of trains. The lower- level model is an optimization model of equilibrium of load factor, which is to determine the optimal formation plans and departure interval. And a nested genetic algorithm is also proposed. The results indicate that when the train formation and frequency is fixed, the average load of the trains under the even headways is 50%, the difference is only 0.8% under the uneven headways. The number of vehicles of two kinds of trains has minor differences can improve the equilibrium of train load factor under even headways. Besides, adjusting the headways between different train formations under uneven headways can realize the equilibrium of load factor in time and space. Copyright © 2019 by Science Press.
引用
收藏
页码：187 / 192and210
相关论文
共 10 条
  • [1] Mao B.H., Zhang Z., Chen Z.J., Et al., A review on operational technologies of urban rail transit networks, Journal of Transportation Systems Engineering and Information Technology, 17, 6, pp. 155-163, (2017)
  • [2] Mao B.H., Liu M.J., Huang R., Et al., Operational Theories and Key Technologies of Rail Transit Networks, (2011)
  • [3] Lei X.Y., Yang G.F., Yi C.Y., Et al., Discussion on flexible formation of rail transit and its characteristics of combined transport organization operational, Railway Transport and Economy, 37, 9, pp. 64-69, (2015)
  • [4] Niu H.M., Zhang M.H., An optimization to schedule train operations with phase-regular framework for intercity rail lines, Discrete Dynamics in Nature and Society, (2012)
  • [5] Deng L.B., Wang F., Zhou Z., Et al., Optimization method of intercity trains through train plan, Journal of Railway Science and Engineering, 10, 6, pp. 97-102, (2013)
  • [6] Yu D.D., Han B.M., Zhang Q., Et al., Optimization method for train plan of urban rail transit based on the flexible length of train formation, Journal of Beijing Jiaotong University, 39, 6, pp. 21-31, (2015)
  • [7] Rong Y.P., Zhang X.C., Bai Y., Et al., Optimization method for train plan of urban rail transit based on hybrid train formation, Journal of Transportation Systems Engineering and Information Technology, 16, 5, pp. 117-122, (2016)
  • [8] Xu D.J., Mao B.H., Lei L.G., Optimization for train plan of full-length and short-turn routing in urban rail transit, Journal of Transportation Systems Engineering and Information Technology, 17, 1, pp. 120-126, (2017)
  • [9] Niu H.M., Chen M.M., Zhang M.H., Optimization theory and method of train operation scheme for urban rail transit, China Railway Science, 32, 4, pp. 128-133, (2011)
  • [10] Oldfield R., Bly P., An analytic investigation of optimal bus size, Transportation Research Part B, 22, 5, pp. 319-337, (1988)
1