Abstract: The passenger flow of high-speed railway (abbreviated as high-speed railway) fluctuates greatly in a day, showing the characteristics of peak, flat peak and low peak. Using the idea of "peak clipping and valley filling", based on time-sharing pricing theory and Logit utility function, considering the behavior factors of passengers in choosing travel modes, as well as the constraints of railway carrying capacity and passenger capacity, this paper established a time-sharing pricing model with the goal of maximizing revenue of high-speed railway enterprises and used genetic algorithm to solve it. The feasibility of the above model and algorithm were verified by a practical example of a railway line. The verification results show that the time-sharing pricing strategy of high-speed rail is helpful to improve the market share of high-speed railway and the passenger revenue of operating enterprises.