Real-Time Scheduling for Trains in Urban Rail Transit Systems Using
Nonlinear Optimization
Reference
Y. Wang,
B. De Schutter,
T.J.J. van den Boom,
B. Ning, and
T. Tang,
"Real-Time Scheduling for Trains in Urban Rail Transit Systems Using
Nonlinear Optimization," Proceedings of the 16th
International IEEE Conference on Intelligent Transportation Systems
(ITSC 2013), The Hague, The Netherlands, pp. 1334-1339, Oct.
2013.
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 trains. Based on the
passenger demand in urban rail transit systems, the optimal departure
times, running times, and dwell times are obtained by solving the
scheduling problem. Three solution approaches are proposed to solve
the real-time scheduling problem for trains: a pattern search method,
a mixed integer nonlinear programming (MINLP) approach, and a mixed
integer linear programming (MILP) approach. The performance of these
three approaches is compared via a case study based on the data of the
Beijing Yizhuang line. The results show that the pattern search method
provides a good trade-off between the control performance and the
computational efficiency.
Downloads
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Bibtex entry
@inproceedings{WanDeS:13-036,
author={Y. Wang and B. {D}e Schutter and T.J.J. van den Boom and B. Ning and T.
Tang},
title={Real-Time Scheduling for Trains in Urban Rail Transit Systems Using
Nonlinear Optimization},
booktitle={Proceedings of the 16th International IEEE Conference on Intelligent
Transportation Systems (ITSC 2013)},
address={The Hague, The Netherlands},
pages={1334--1339},
month=oct,
year={2013}
}
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