灵活编组与短交路策略下双向中断地铁线列车运行调整OA

Metro lines connecting urban centers and suburbs often face imbalanced spatiotemporal passenger flows,prompting innovative solutions like unpaired train operation plans and flexible train composition technologies to optimize capacity allocation across different service periods.However,operational disruptions introduce complex challenges including rolling stock circulation imbalance and train composition adaptation failures,particularly for metro lines employing unpaired operations and flexible train compositions.This study developed a disruption recovery approach combining flexible train compositions with short-turning strategies,formulated as a multi-objective optimization model integrating rolling stock circulation,timetable adjustment and composition planning and solved via an efficient Lagrangian Relaxation algorithm.Empirical analysis based on Shanghai Metro operational data demonstrates significant improvements:(1)the proposed LR algorithm achieves 66%faster computation than Gurobi with optimality gaps below 3.5%;(2)service cancellations reduce by 49%and timetable deviations by 46%compared to conventional methods,respectively;(3)rolling stock utilization is significantly improved through dynamic coupling and decoupling operations.The research provides both theoretical and practical guidance for metro disruption management in complex operational environments.