Service-oriented train timetabling with collaborative passenger flow control on an oversaturated metro line: An integer linear optimization approach

With the drastic increase of travel demands in urban areas, more and more metro lines are nowadays suffering from oversaturated situations, leading to the accumulation of passengers on platforms with potential accident risks. To further improve the service quality and reduce accident risks, this paper proposes an effective method for collaboratively optimizing the train timetable and accurate passenger flow control strategies on an oversaturated metro line. Through considering the dynamic characteristics of passenger flow, a rigorous integrated integer linear programming model is firstly formulated to minimize the total passenger waiting time at all of involved stations, in which the train timetable provides a service-oriented operation plan and optimal passenger flow control is imposed to avoid congestion on platforms within the transportation capacities. To solve the problem of interest efficiently, a hybrid algorithm, which combines an improved local search and CPLEX solver, is designed to search for high-quality solutions. Finally, two sets of numerical experiments, including a small-scale case and a real-world instance with operation data of the Beijing metro system, are implemented to demonstrate the performance and effectiveness of the proposed approaches.