Optimization method for maximizing capacity utilization of high-speed railway train timetable based on node routing model

The increasing passenger demand on certain high-speed railway lines has resulted in strained capacity utilization, posing a challenge for railway operators to optimize train timetables to maximize capacity utilization. This paper investigates the impact of train path sequences on section carrying capacity, as well as how train paths utilize time-space resources of train timetables. The problem of scheduling train timetables is transformed into the problem of node routing, where nodes represent train paths, directed arcs depict the sequential connections between train paths. A train timetable optimization model based on node routing is constructed, with the objective of maximizing the number of trains and the constraint that the total arc weight does not exceed total amount of time-space resources on the train timetable. Then considering the characteristics of the model, this paper designs an optimization algorithm for train timetables, which includes modules for designing train overtaking combinations, quantifying time-space resources, optimizing train path sequences, and scheduling train timetables. The algorithm is tested on the Shanghai-Hangzhou High-speed Railway in China. The computational results prove that the optimization method based on node routing can help railway operators improve the capacity utilization level of high-speed railways. Further, we design a series of experiments to study the impact of train headway times, train running speed, and other factors on the section carrying capacity, reveal the impact mechanisms of these train timetable factors on section carrying capacity, and propose optimization strategies for high-speed train timetables to railway operators.