An Integrated Optimization Method of High-Speed Railway Rescheduling Problem at the Network Level

被引:1
|
作者
Zhao, Wenqiang [1 ]
Zhou, Leishan [1 ]
Guo, Bin [1 ,2 ]
Yue, Yixiang [1 ,2 ]
Han, Chang [1 ]
Wang, Zeyu [3 ]
Mo, Yuxin [1 ]
机构
[1] Beijing Jiaotong Univ, Sch Traff & Transportat, Beijing 100044, Peoples R China
[2] Beijing Jiaotong Univ, Frontiers Sci Ctr Smart High Speed Railway Syst, Beijing 100044, Peoples R China
[3] Infrastructure Investment Co Ltd, Beijing 100101, Peoples R China
来源
APPLIED SCIENCES-BASEL | 2023年 / 13卷 / 19期
关键词
high-speed railway network; train rescheduling; emergency management; integrated optimization method; GENETIC ALGORITHM; TRAIN;
D O I
10.3390/app131910695
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
For high-speed railway operations at the network level, unforeseen events that lead to operation interruptions are inevitable, which should be handled within a short period of time to reduce the influence of the events as much as possible. This paper introduces an integrated optimization method to deal with rescheduling problems at the railway network level under emergencies, rescheduling the train timetable, and utilizing the train sets. train set A three-objective optimization model is proposed with the aim of minimizing additional operation costs, total delay, and the number of transfer passengers. Then, an algorithm based on NSGA-III is proposed to solve the model. Computational experiments on real data are conducted to show the adaptability of the model and algorithm. The average optimization rate of the three objectives is 12.12%, 14.12%, and 10.57%, indicating the effectiveness of the method. Moreover, more experiments on a railway network in China are being conducted to analyze which section and which time have the greatest impact on the railway network when emergencies occur. According to the experiment, the bottleneck section is section 15, and the bottleneck time is 11:00 am. In addition, the importance of all the depots is discussed, and depot II is selected as the most important depot.
引用
收藏
页数:33
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