Collaborative Optimization of Train Scheduling and Passenger Flow Control with Adjustable Dwell Time on a Congested Metro Line

Metro lines in megacities often experience extreme congestion during peak hours, causing passengers to strand on platforms and pose serious operational risks. This paper formulates a mixed-integer nonlinear programming model (MINP) for the train scheduling and passenger flow control coordination problem with adjustable dwell time on overcrowded metro lines. It can offer a service-oriented schedule plan and implements the effective passenger flow control strategy to reduce platform congestion while maintaining transportation capacity. By employing a linearization method, this paper transformes the proposed model into a linear program that can be efficiently solved via Gurobi. Finally, numerical experiments show that the total waiting time of passengers is reduced by 40.8%, which can effectively reduce rail traffic congestion, and verify the effectiveness of the model.