Daily Line Planning Optimization for High-Speed Railway Lines

Daily line planning in the operation stage should satisfy fluctuating travel demand on different days and ensure stability. In this paper, we propose an approach of daily optimization for high-speed railway (HSR) lines to trade off system costs The plan is optimized by adjusting reference based baseline plan. A bi-level programming model constructed Stackelberg game theory describe interaction conflicts between companies passengers. We thought “trigger decision, space-time coupling joint iteration” solve under framework Simulated Annealing Algorithm (SAA). case study Beijing–Shanghai HSR Line demonstrates that adjusted can not only optimize but also It provide sufficient transit capacity requirements passengers present obvious advantage cost reduction.