A Capacity-Utilization-Oriented Stop Planning Approach for High-Speed Railway Network with Stop Distribution Balance

Stop planning is aimed to provide proper services for passenger demand, but diverse stop patterns lead to differences in stop density and travel speeds, impacting the utilization of line capacity. This paper incorporates capacity utilization into stop planning in the strategic line planning stage to trade off the matching between supply and demand and the stop distribution balance among trains. A bi-level programming model is established to formulate the Stackelberg game relation between supply and demand, where the stop distribution imbalance and the passenger travel inefficiency are measured. An adaptive hybrid solving algorithm combined with Genetic Algorithm and Simulated Annealing Algorithm is proposed, with several adaptive operations according to the problem characteristics and optimization degree to improve searching efficiency. A case study on the local network of Beijing–Shanghai High-speed Railway Line demonstrates that the proposed approach can not only mitigate the stop distribution imbalance, but also improve the travel efficiency of passengers, indicating that it can benefit the simultaneous improvement of capacity utilization and service level.