Aiming to ensure the feasibility of the optimized train stop planning, a novel optimization method is proposed in this paper, which conducts the simulation experiment of train scheduling compilation based on the train stop planning, and then takes the evaluation of train scheduling as the basis of the optimization of train stop planning. Specifically, random interference and the principle of dynamic matching of buffer time distribution and train stop planning are embedded into the simulation experiment to make it closer to the reality. The resources occupied and stability of train scheduling are adopted as the objective function, and passenger demand, number of stops are used as constrains. Genetic algorithm and the resolution strategy of constrains conflict are designed to solve the model. Finally, numerical experiments are implemented based on the operational data of Shanghai-Nanjing intercity railway. The result shows that the optimized train stop planning makes the carrying capacity improved by 8.47% under the premise of ensuring good stability, which verifies the effectiveness and efficiency of the proposed approach.

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