Railway crew rescheduling with retiming

Railway operations are disrupted frequently. For example, the Dutch railway network experiences about three large disruptions per day on average. In a disrupted situation, a railway operator needs to quickly adjust the timetable and the resource schedules. Usually the timetable, the rolling stock and the crew schedule are recovered in a sequential way. In this paper, we model and solve the crew rescheduling problem with retiming. This problem extends the crew rescheduling problem by the possibility to slightly delay the departure of some trains, so that some more flexibility in the crew scheduling process is obtained. Our algorithm focuses on rescheduling the duties of the train drivers. It is based on column generation techniques combined with Lagrangian heuristics. In order to prevent a large increase in computation time, retiming is allowed only for a limited number of trains for which it seems promising. Computational experiments with train driver duties and real-life disruption data show that, compared to the classical approach, it is possible to find better solutions by using crew rescheduling with retiming. Research highlights ► We propose a new column generation based algorithm for railway crew rescheduling. ► The approach is able to solve the problem within minutes. ► We compare our new approach with retiming with an approach without retiming. ► Allowing retiming leads to better crew schedules with less canceled tasks.

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