Abstract: In view of the general problems of unbalanced development of China’s multi-airport system and high degree of homogenization of routes, a flight schedule optimization model was established to maximize the flight punctuality rate, airline market share, passenger loss time and flight function positioning index, and the flights with poor operation effect of the first level international hub airport were allocated to the surrounding airports. Under the conditions of meeting the takeoff and landing capacity constraints, flight uniqueness and flight continuity of each airport in the multi-airport system, an improved particle swarm optimization algorithm was designed to solve the problem. The flight schedule of Yangtze River Delta multi-airport system was taken as an example to verify. The research shows that the proposed model can effectively adjust the inefficient flights of the hub airport to the surrounding airports, which makes the flight distribution of each airport in the multi-airport system more balanced and effectively controls the change trend of flight sorties in each period, and the optimization effect is significant.

Key words: traffic and transportation engineering; flight schedule optimization; multi-airport system; particle swarm optimization algorithm

摘要： 针对我国机场群发展不平衡、航线同质化程度高等问题，建立了以航班准点率、航空公司市场份额、旅客损失时间和航班功能定位指标最大化的航班时刻优化模型，将一级国际枢纽机场运行效果差的航班分配至周边机场。笔者在满足机场群内各机场起降容量限制、航班唯一性和航班连续性的条件下，设计改进的粒子群优化算法进行求解。以长三角机场群的航班时刻资源为例进行实例验证。研究表明：模型能够有效调整枢纽机场的低效航班至周边机场，使得机场群内各机场航班分布较为均衡，有效控制各时段航班架次的变化趋势，优化效果显著。

关键词: 交通运输工程；航班时刻优化；机场群；粒子群优化算法