交通运输系统工程与信息

交通运输系统工程与信息 ›› 2023, Vol. 23 ›› Issue (5): 312-320.DOI: 10.16097/j.cnki.1009-6744.2023.05.032

• 运输组织优化理论与方法 • 上一篇    

考虑潜在冲突的进离场航班协同排序

王建忠*1，丁小芹1，王树伟2   

  1. 1. 中国民航大学，空中交通管理学院，天津 300300；2. 民航天津空中交通管理分局，天津 300300
  • 收稿日期:2023-06-24 修回日期:2023-08-18 接受日期:2023-09-08 出版日期:2023-10-25 发布日期:2023-10-23
  • 作者简介:王建忠(1981- )，男，内蒙古包头人，副教授，博士
  • 基金资助:
    天津市应用基础多元投入基金重点项目(21JCZDJC00780)

Collaborative Sequencing of Arrival and Departure Aircraft Considering Potential Conflicts

WANG Jian-zhong*1, DING Xiao-qin1, WANG Shu-wei2   

  1. 1. College of Air Traffic Management, Civil Aviation University of China, Tianjin 300300, China; 2. Tianjin Air Traffic Management Sub-bureau, Tianjin 300300, China
  • Received:2023-06-24 Revised:2023-08-18 Accepted:2023-09-08 Online:2023-10-25 Published:2023-10-23
  • Supported by:
    Key Program of Tianjin Science and Technology Plan (21JCZDJC00780)

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摘要： 考虑进离场排序中潜在冲突引起的管制员工作负荷增加以及排序结果的可执行性等问题，本文提出基于多目标时间索引模型的进离场航班排序方法。用潜在冲突时间长度来表征管制员解决冲突的负荷大小。以延误时间和解决冲突负荷最小为目标函数，引入时间索引模型，将时间段离散化为一定步长的时隙，为每架航班分配着陆、起飞时隙，而非固定的时间点，从而提高排序结果的可执行性。根据模型的具体特征，设计遗传算法，利用天津滨海国际机场数据，求解验证模型的有效性。实验结果表明：模型在各种权重组合下，对减少航班总延误时间和管制员解决潜在冲突的负荷均有良好的优化效果；在权重组合为0.2-0.8的条件下，相比于实际运行情况和先到先服务策略，航班延误的优化率为 11.25%和 11.87%，管制员解决冲突负荷的优化率为 28.70%和37.90%；权重组合为0.1-0.9时，航班延误的优化率为9.70%和10.34%，管制员解决冲突负荷的优化率达45.37%和52.42%。因此，模型在减少航班延误的同时也极大程度上减少了潜在冲突时间，降低了管制员的工作负荷，提高了终端区的运行效率和安全。

关键词: 航空运输, 时间索引模型, 遗传算法, 进离场排序, 空中交通管理

Abstract: This paper proposes an arrival and departure flight sequencing method based on a multi-objective time-indexed model to address the increase in controller workload caused by potential conflicts and improve the enforceability of sequencing results. The length of potential conflict time is used to quantify the controller's workload in resolving conflicts. Taking the minimum delay time and conflict resolution load as the objective function, a time-indexed model is introduced to discretize the time period into time slots, allowing for the allocation of landing and take-off time slots for each flight instead of fixed time points, thereby enhancing the enforceability of the sorting results. A genetic algorithm is designed to optimize the model, and the effectiveness of the model is verified using data from Tianjin Binhai International Airport. Experimental results demonstrate that the model effectively reduces total flight delay time and the controller's workload in solving potential conflicts under different weight combinations. Compared to actual operation scenarios and the first-come-first-served strategy, the optimization rate for flight delays is 11.25% and 11.87% for a weight combination of 0.2-0.8, and 9.70% and 10.34% for a weight combination of 0.1-0.9. The optimization rates for the controller's conflict resolution load are 28.70% and 37.90% , and 45.37% and 52.42% respectively. Therefore, in addition to reducing flight delays, the model significantly reduces potential conflict time, alleviates controller workload, and improves operational efficiency and safety in the terminal area.

Key words: air transportation, time-indexed model, genetic algorithm, arrival and departure aircraft sequencing, air traffic management

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