机场群离港航班时刻稳定性评估及优化

Evaluation and optimization of departure flight schedule stability of airport group

随着中国航空运输量的不断增加,机场群航班时刻资源日益稀缺、航班延误严重等问题也逐渐显现,有必要深入研究机场群的航班时刻优化问题。在明确机场群离港航班时刻稳定性概念基础上,提出离港航班延误率、平均延误时间等共6项机场群离港航班时刻稳定性评估指标,并运用改进的逼近理想解排序(TOPSIS)法对稳定性进行质量评估。建立机场群离港航班时刻优化模型,选择改进粒子群算法来实现对该模型的优化,并以稳定性质量为标准对优化前后航班计划进行比较。以京津冀机场群为例进行验证,仿真结果表明:所提优化模型和算法能够降低北京首都国际机场离港航班平均延误时间18.8 s,降低平均延误率9.9%;繁忙航线平均延误时间降低12.7 s,平均延误率降低3.0%;有效降低了京津冀机场群整体延误水平,提高机场群离港航班时刻稳定性。

As China’s aviation traffic keeps growing,issues including dwindling flight schedule resources and major flight delays in airport clusters are rapidly becoming more and more prevalent.It is necessary to thoroughly study flight schedule optimization in airport groups.On the basis of defining the concept of departure flight schedule stability of airport groups,this paper puts forward six evaluation indexes of departure flight schedule stability of airport groups,such as departure flight delay rate and average delay time,and evaluates the stability quality by using improved TOPSIS(a technique for order preference by similarity to ideal solution).Following the establishment of the airport group’s departure flight schedule optimization model and the selection of an improved particle swarm optimization algorithm to optimise the model,the flight plans before and after optimization are contrasted using the stability quality as the benchmark.Finally,taking Beijing-Tianjin-Hebei airport group as an example,the simulation results show that the proposed optimization model and algorithm can reduce the average delay time of departure flights at Beijing airport by 18.8 s and the average delay rate by 9.9%;The average delay time of busy routes is reduced by 12.7 s,and the average delay rate is reduced by 3.0%,which effectively reduces the overall delay level of Beijing-Tianjin-Hebei airport group and improves the stability of departure flight schedule of the airport group.