Rescheduling Railway Traffic on Real Time Situations Using Time-Interval Variables

摘要

In the railway domain, the action of directing the traffic in accordance with an established timetable is managed by a software. However, in case of real time perturbations, the initial schedule may become infeasible or suboptimal. Subsequent decisions must then be taken manually by an operator in a very limited time in order to reschedule the traffic and reduce the consequence of the disturbances. They can for instance modify the departure time of a train or redirect it to another route. Unfortunately, this kind of hazardous decisions can have an unpre-dicted negative snowball effect on the delay of subsequent trains. In this paper, we propose a Constraint Programming model to help the operators to take more informed decisions in real time. We show that the recently introduced time-interval variables are instrumental to model this scheduling problem elegantly. We carried experiments on a large Belgian station with scenarios of different levels of complexity. Our results show that the CP model outperforms the decisions taken by current greedy strategies of operators.