机场群终端区离港航班协同排序方法研究
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南京航空航天大学民航学院

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国家重点基础研究发展计划(973计划)


Research on Collaborative Sequencing Methods for Departing Flights in Airport Cluster Terminal Area
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    摘要:

    当前空中交通领域中,机场群系统频繁出现的飞行冲突、离港航班延误等问题日益成为影响航班运行效率和旅客满意度的关键因素。鉴于此,本研究旨在探讨机场群系统中离港航班的协同排序问题。在考虑机场群系统资源约束的基础上,引入“离港航班满意度”这一概念,以离港航班总延误最小化、所有机场航班平均满意度之和最大化以及机场群系统内机场公平性的整体度量最小化为优化目标,建立机场群终端区离港航班协同排序模型,设计带精英策略的非支配排序多目标遗传算法,求解机场群终端区离场航班协同排序问题的Pareto最优解。以京津地区的三个机场终端区为例进行了实例分析,验证了所提出模型和方法的有效性。实验结果表明,与先到先服务方案相比较,航班总延误从7796秒减少至5029秒,降低了35.3%,平均每一架航班延误时间从159秒降到103秒,航班满意度平均满意度达到0.7867,机场群中机场公平性的整体度量为0.0044,所提出的优化方法能够显著降低机场群系统中离港航班的总延误,提高航班总满意度,实现资源的公平高效使用。

    Abstract:

    In the current domain of air traffic, frequent flight conflicts and departure flight delays within airport systems are increasingly becoming key factors that affect the efficiency of flight operations and passenger satisfaction. In light of this, the present study aims to explore the collaborative sequencing problem of departure flights within airport systems. By considering the resource constraints of airport systems, the concept of "departure flight satisfaction" is introduced. The objectives of optimization include minimizing the total delay of departure flights, maximizing the sum of average satisfaction across all flights in airports, and minimizing the overall measure of fairness within the airport system. A collaborative sequencing model for departure flights in the terminal area of airport clusters is established, and an elitist strategy-based non-dominated sorting genetic algorithm is designed to solve the Pareto optimal solution for the collaborative sequencing problem of departure flights in the terminal area of airport clusters. An empirical analysis was conducted using the terminal areas of three airports in the Beijing-Tianjin region as examples, validating the effectiveness of the proposed model and method. The experimental results show that compared to the first-come-first-served scheme, the total flight delay was reduced from 7,796 seconds to 5,029 seconds, a decrease of 35.3%, with the average delay per flight dropping from 159 seconds to 103 seconds. The average satisfaction of flights reached 0.7867, and the overall measure of fairness among airports in the cluster was 0.0044. The proposed optimization method can significantly reduce the total delay of departure flights in airport systems, improve overall flight satisfaction, and achieve the fair and efficient use of resources.

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  • 收稿日期:2024-04-07
  • 最后修改日期:2024-05-12
  • 录用日期:2024-05-13
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