Joint train line planning and timetabling of intercity high-speed rail with actual time-dependent demand

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Intercity high-speed rail (HSR) is a type of mass transit built in densely populated metropolitan areas and has become an essential part of sustainable transportation systems in some countries. One of the most challenging problems is how to jointly optimize the train line plan and timetable with simultaneous consideration of the system efficiency, cost, and level of service. In this paper, we focus on optimizing the train line plan and timetable of intercity HSR given actual time-dependent demand while appropriately considering the operational constraints including overtaking. First, we formulate the optimization problem as a mixed integer nonlinear programming (MINLP). Its objective is to minimize the total system cost comprised of the trains’ fixed and variable operation costs, passengers’ travel time cost, and penalties for passengers’ departure time deviation and passengers’ failing to board a train. We then design a double-layer simulated annealing (SA) algorithm, in which the inner layer algorithm optimizes the stop plan, the departure and arrival times at each station, while the outer layer algorithm optimizes the number of trains, their origin–destination stations, and their departure times at origin stations. Next a case study is conducted on Shanghai-Nanjing intercity HSR using actual time-dependent demand. The numerical results show that the proposed model can help significantly reduce the total number of trains used by increasing the average seat occupancy, while creating little impact on the average passenger travel time and departure time. The study provides valuable guidance for optimizing HSR train line plan and timetable based on real-world time-dependent demand.