The traditional optimization and adjustment process of train operation plan is relatively lagging behind changes in passenger flow. When the daily passenger flow changes, the traditional process of optimizing and adjusting train operation plan cannot timely meet passenger flow demands while having minimal changes in passenger transportation and service organization. Therefore, this study adjusts the train operation plan by minimizing adjustments while meeting passenger flow demands. It constructs a two-layer adjustment model for high-speed train operation plan based on passenger flow demands: The upper layer aims to adaptability and optimal adjustment weighting, and the lower layer focuses on minimizing the total impedance of the train service network. An annealing-evolution algorithm is designed to solve the train operation plan constructed in this study. Finally, by building a simple high-speed railway line and using initial OD passenger flow data and initial train operation plan, the model and algorithm's effectiveness are validated by adjusting the train operation plan based on two fluctuations of OD passenger flow using the adjustment model.