DocumentCode :
3603641
Title :
Efficient Real-Time Train Scheduling for Urban Rail Transit Systems Using Iterative Convex Programming
Author :
Yihui Wang ; Bin Ning ; Tao Tang ; van den Boom, Ton J. J. ; De Schutter, Bart
Author_Institution :
State Key Lab. of Rail Traffic Control & Safety, Beijing Jiaotong Univ., Beijing, China
Volume :
16
Issue :
6
fYear :
2015
Firstpage :
3337
Lastpage :
3352
Abstract :
The real-time train scheduling problem for urban rail transit systems is considered with the aim of minimizing the total travel time of passengers and the energy consumption of the operation of trains. Based on the passenger demand in the urban rail transit system, the optimal departure times, running times, and dwell times are obtained by solving the scheduling problem. A new iterative convex programming (ICP) approach is proposed to solve the train scheduling problem. The performance of the ICP approach is compared with other alternative approaches, i.e., nonlinear programming approaches, a mixed-integer nonlinear programming (MINLP) approach, and a mixed-integer linear programming (MILP) approach. In addition, this paper formulates the real-time train scheduling problem with stop-skipping and shows how to solve it using an MINLP approach and an MILP approach. The ICP approach is shown, via a case study, to provide a better tradeoff between performance and computational complexity for the real-time train scheduling problem. Furthermore, for the train scheduling problem with stop-skipping, the MINLP approach turns out to have a good tradeoff between the control performance and the computational efficiency.
Keywords :
computational complexity; convex programming; integer programming; iterative methods; linear programming; minimisation; railways; scheduling; ICP; MILP; MINLP; computational complexity; iterative convex programming; mixed-integer linear programming; mixed-integer nonlinear programming; stop-skipping; train scheduling problem; travel time minimization; urban rail transit system; Energy consumption; Iterative methods; Optimal scheduling; Rail transportation; Real-time systems; Scheduling; Real-time train scheduling; stop-skipping; urban rail transit;
fLanguage :
English
Journal_Title :
Intelligent Transportation Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
1524-9050
Type :
jour
DOI :
10.1109/TITS.2015.2445920
Filename :
7154484
Link To Document :
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