A Two-Objective Timetable Optimization Model in Subway Systems

2014 ◽  
Vol 15 (5) ◽  
pp. 1913-1921 ◽  
Author(s):  
Xin Yang ◽  
Bin Ning ◽  
Xiang Li ◽  
Tao Tang
Author(s):  
Bo Jin ◽  
Xiaoyun Feng ◽  
Qingyuan Wang ◽  
Pengfei Sun ◽  
Qian Fang

The rapid development of metro transit systems brings very significant energy consumption, and the high service frequency of metro trains increases the peak power requirement, which affects the operation of systems. Train scheduling optimization is an effective method to reduce energy consumption and substation peak power by adjusting timetable parameters. This paper proposes a train timetable optimization model to coordinate the operation of trains. The overlap time between accelerating and braking phases is maximized to improve the utilization of regenerative braking energy (RBE). Meanwhile, the overlap time between accelerating phases is minimized to reduce the substation peak power. In addition, the timetable optimization model is rebuilt into a mixed integer linear programming model by introducing logical and auxiliary variables, which can be solved by related solvers effectively. Case studies based on one of Guangzhou Metro Lines indicate that, for all-day operation, the utilization of RBE would likely be improved on the order of 23%, the substation energy consumption would likely be reduced on the order of 14%, and the duration of substation peak power would likely be reduced on the order of 66%.


2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Renjie Zhang ◽  
Shisong Yin ◽  
Mao Ye ◽  
Zhiqiang Yang ◽  
Shanglu He

Nowadays, an express/local mode has be studied and applied in the operation of urban rail transit, and it has been proved to be beneficial for the long-distance travel. The optimization of train patterns and timetables is vital in the application of the express/local mode. The former one has been widely discussed in the various existing works, while the study on the timetable optimization is limited. In this study, a timetable optimization model is proposed by minimizing the total passenger waiting time at platforms. Further, a genetic algorithm is used to solve the minimization problems in the model. This study uses the data collected from Guangzhou Metro Line 14 and finds that the total passenger waiting time at platforms is reduced by 9.3%. The results indicate that the proposed model can reduce the passenger waiting time and improve passenger service compared with the traditional timetable.


Author(s):  
Xin Yang ◽  
Bin Ning ◽  
Xiang Li ◽  
Tao Tang ◽  
Xiaomei Song

Since the regenerative braking technique can recover considerable electricity from braking trains, it is maturely applied in subway systems. Generally speaking, except a small part of the recovery energy is used by the on-board auxiliary services, most of them is fed back into the overhead contact line. If the feedback energy cannot be absorbed by adjacent accelerating trains timely, it will be consumed by resistances. For maximizing the utilization of recovery energy, this paper proposes a timetable optimization model to coordinate the accelerating and braking processes of up trains and down trains. Firstly, we analyze the coordinating rules. Secondly, we propose an integer programming model to maximize the utilization of recovery energy with headway time and dwell time control. Furthermore, we design a genetic algorithm to solve the optimal timetable. Finally, we conduct numerical examples based on the operation data from Beijing Yizhuang subway line of China. The results illustrate that the proposed model can significantly save energy by 21.58% compared with the current timetable.


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