A Two-stage Stochastic Programming Approach for Timetable Rescheduling with Reassignment of Rolling Stock under Uncertain Disruptions

Abstract

High-speed railways (HSRs) are susceptible to disruptions that can cause trains to deviate from their operation plan and, in severe cases, even disrupt the rolling stock plan. The duration of disruptions is often highly uncertain and unpredictable. It makes the timetable rescheduling problem even more challenging. This paper proposes an Event-Activity Network-based rescheduling model to solve the timetable rescheduling problem for HSRs with the reassignment of rolling stock under uncertain disruption. To deal with the uncertainty, the uncertain disruption is regarded to have several possible deterministic scenarios. A two-stage stochastic programming approach is utilized to make a conflict-free rescheduling scheme for all possible scenarios within the minimum end time. A case study based on the practical data of the Beijing-Tianjin Intercity Railway is carried out to demonstrate the effectiveness of the proposed method. The results show that the proposed method can decrease the total delay and cancellations, and improve the robustness of rescheduling schemes.