Train Routing and Track Allocation Optimization Model of Multi-Station High-Speed Railway Hub

Abstract

A multi-station high-speed railway hub is the interaction of multiple high-speed railway lines, and its operation determines the efficiency of the whole network. In this study, we focus on the train routing problem for a multi-station railway hub and propose a flexible scheme to improve the capacity utilization. Based on the flexible scheme, a mixed-integer programming node-arc model is formulated to minimize the total cost of train and passenger routes. Specifically, for diversifying the train routes, we consider the individual train rather than the train flow as the basic unit, which differs from the approach in previous studies. For each train route, in addition to the macro-scale route between stations, the micro-scale track allocation inside stations is also considered. Afterward, the optimization solver Gurobi is used to solve the model and obtain the optimization scheme. A case study based on real data from the Zhengzhou railway hub in China is implemented to evaluate the effectiveness of the optimization model. By comparing the optimization scheme with the fixed scheme and the sequential scheme, the results show our method could reduce the total cost by 29.35% and 22.58%, and the line and track capacity utilization of the optimization scheme is more reasonable. We provide some suggestions to help railway managers improve the operation efficiency and service quality of multi-station high-speed railway hubs.