Optimization of crew rescheduling in urban rail transit under emergency conditions

This study examines the crew rescheduling problem of urban rail transit in the context of deviations from planned timetables caused by emergencies. The problem is formulated as a graph-based heterogeneous fleet vehicle routing problem like problem. A nonlinear binary integer programming model is developed with objectives of minimizing the deviation from the original timetable and minimizing the number of backup crew members deployed. An improved ant colony optimization algorithm is proposed to plan the subsequent scheduling on the day of the incident. Experimental results demonstrate that the model efficiently produces optimal rescheduling solutions while adhering to operational constraints. When the rescheduling time span is relatively short, the adjusted crew schedule can completely avoid unnecessary plan deviations. When the time span approaches an entire day, the algorithm introduces only a small number of backup crew numbers, and the deviation ratio between the original crew plan and the rescheduled one is less than 5%.