Multi-Objective Optimisation of Timetable for Urban Rail Transit during the End-of-Operation Period for Large-Scale Events

This study proposes a timetable multi-objective optimisation model for urban rail transit during the end-of-operation period, addressing dynamic passenger demand under limited train capacity. The model simultaneously minimises the unreachable rate of last-train origin-destination (OD) points and passenger flow-induced congestion at the station. Key decisions involve optimising dwell times and headways while incorporating dynamic transfer spatiotemporal constraints and train capacity limitations. To resolve the computational complexity from non-convex and non-linear terms, a multi-objective whale optimisation algorithm is employed. Case studies under large-scale events reveal that moderately extending dwell times (1.5-2 minutes) alleviates congestion, while excessive extensions prove ineffective due to line length limitations. For headways, 8-10 minutes generally optimises departure frequency, though specific Pareto-optimal solutions may flexibly adopt 4-8 minute intervals. The findings enable operators to balance accessibility and congestion mitigation based on event characteristics, enhancing operational efficiency and passenger satisfaction. The research provides actionable strategies for improving last-train transfer coordination and station flow management during special operational periods.