为解决目前中国机场中转衔接效率不高的问题，通过分析影响机场航班中转衔接性的因素，基于航班波的理论定义命中的概念及其计算方法，构建了以枢纽一日中转衔接命中数最大化为目标，同时考虑时间约束、绕航约束和跑道容量约束的时刻调整模型。设计自适应模拟退火遗传算法对模型进行求解，在自适应遗传算法中引入模拟退火的思想提高算法的全局搜索能力和收敛速度，并与传统遗传算法和模拟退火算法进行对比。对首都机场一日起降航班数据进行实证分析，分别求解出3种时间窗调整时长下的最优命中数，并迭代出相应的航班时刻表。结果表明，改进算法能在更短时间内获得较高质量的近优解，优化后的航班时刻呈现出明显的波形结构，机场的中转衔接性能得到了有效提升。

In order to solve the problem of inefficient transit connection at domestic airports, by analyzing the factors affecting the airport flight transfer connection, the concept and calculation method of hit were defined based on the theory of flight wave. On this basis, a time adjustment model was constructed with the goal of maximizing the number of hits of one-day transit connection at the hubs, and taking the time constraints, the detour constraints and the runway capacity constraints into account at the same time. An adaptive simulated annealing genetic algorithm was designed to solve this model, and the idea of simulated annealing was introduced into the adaptive genetic algorithm to improve the global search capability and convergence speed of the algorithm, and compared with traditional genetic algorithm and simulated annealing. Through the empirical analysis of the one-day flight data of the capital airport, the optimal number of hits under the three kinds of time window adjustment durations was solved respectively, and the corresponding flight schedules were iterated. The results show that the improved algorithm can obtain high-quality near-optimal solutions in a shorter time. The optimized time structure presents an obvious waveform structure, and the transit connection performance of the airport has been effectively improved.