Abstract: In order to improve the punctuality rate and connectivity efficiency of hub airport flight operation, based on the definition of individual and total number of transit connection hits of inbound flights, a dual objective slot planning and adjustment model was established, with the goal of maximizing the number of transit connection hits and minimizing the amount of time adjustment and with the constraint conditions of the unplanned delays, runway capacity, and corridor opening capacity. Particle swarm optimization algorithm and linear programming algorithm were used to solve. The proposed model and algorithm were validated with an example of adjusting the flight schedule of Daxing Airport, and the influencing factors of the number of transit connection hits were analyzed by numerical simulation combined with correlation coefficient analysis method. The research results show that the proposed schedule adjustment method can effectively eliminate the delay caused by unreasonable planning, and the number of transit connection hits after optimization is significantly increased. The proposed schedule adjustment method provides a theoretical basis for improving the transit connectivity of hub airports and establishes a benchmark for the comparison of transit connectivity between different airports.

Key words: air transportation engineering; number of transit connection hits; particle swarm optimization; slot structure optimization; correlation analysis

摘要： 为改善枢纽机场航班运行的准点率和衔接效率，在定义个别和总进港航班的中转衔接命中数基础上，构建了以中转衔接命中数最大化、时刻调整量最小化为目标，以无计划延误、跑道容量和走廊口容量为限制条件的双目标时刻规划调整模型。采用粒子群算法和线性规划两种算法进行求解，以大兴机场航班时刻表的调整实例来验证该模型和算法，并用数值模拟结合相关系数分析法分析了中转衔接命中数的影响因素。研究结果表明：该时刻调整方法能有效地消除因计划不合理而导致的延误，同时优化后的中转衔接命中数显著提高；为提高枢纽机场中转衔接性提供了理论基础，也为不同机场间的中转衔接性比较建立了基准。

关键词: 航空运输工程；中转衔接命中数；粒子群算法；时刻结构优化；相关性分析