There usually exists a high density of traffic through bottleneck sections of mainline railways, where a perturbation of one single train could result in long consequential delays across a number of trains. In the event of disturbances, rescheduling trains approaching the bottleneck will be necessary to increase the throughput of the section. To model the real-time train rescheduling problems around bottleneck sections, a mixed-integer programming model is presented in this paper. An innovative improved algorithm (DE_JRM) is developed to solve the problem. The model and the algorithms are validated with a case study using Monte Carlo methodology, which demonstrates that the proposed algorithm can reduce the weighted average delay and satisfy the requirements of real-time traffic control applications.
Modeling and Solving Real-Time Train Rescheduling Problems in Railway Bottleneck Sections
2015
Aufsatz (Zeitschrift)
Englisch
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