融合经济性与鲁棒性的多目标停机位动态分配方法

doi:10.16097/j.cnki.1009-6744.2025.04.030

交通运输系统工程与信息 ›› 2025, Vol. 25 ›› Issue (4): 326-336.DOI: 10.16097/j.cnki.1009-6744.2025.04.030

融合经济性与鲁棒性的多目标停机位动态分配方法

杜婧涵¹ ，李佳祥¹ ，程擎¹ ，朱新平¹，尹嘉男² ，张魏宁^*1

1. 中国民用航空飞行学院，空中交通管理学院，四川广汉618307；2.南京航空航天大学，民航学院，南京211106

收稿日期:2025-05-14 修回日期:2025-06-24 接受日期:2025-07-07 出版日期:2025-08-25 发布日期:2025-08-25
作者简介:杜婧涵(1993—)，女，吉林长春人，讲师，博士。
基金资助:
中央高校基本科研业务费专项资金 (25CAFUC04062)；四川省民航飞行技术与飞行安全工程技术研究中心开放课题(GY2024-03B)。

A Multi-objective Dynamic Gate Assignment Method Integrating Economy and Robustness

DU Jinghan¹, LI Jiaxiang¹, CHENG Qing¹, ZHU Xinping¹, YIN Jianan², ZHANG Weining^*1

1. College of Air Traffic Management, Civil Aviation Flight University of China, Guanghan 618307, Sichuan, China; 2. School of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China

Received:2025-05-14 Revised:2025-06-24 Accepted:2025-07-07 Online:2025-08-25 Published:2025-08-25
Supported by:
Fundamental Research Funds for the Central Universities of Ministry of Education of China (25CAFUC04062)；Open Fund Project of Sichuan Provincial Engineering Technology Research Center for Civil Aviation Flight Technology and Safety (GY2024-03B)。

摘要/Abstract

摘要： 针对民航业复苏背景下停机位资源紧张与动态调度需求，本文提出融合经济性与鲁棒性的停机位分配多目标优化模型。首先，构建包含滑行油耗成本、停机位服务成本和空闲时间成本的综合经济性目标函数；进而，提出回溯混合粒子群算法(Backtracking-HybridParticle Swarm Optimization, BH-PSO)缓解传统粒子群算法(Particle Swarm Optimization, PSO)对参数初始化过度依赖问题，提升全局搜索能力。此外，针对航班时刻不确定性问题，进一步提出基于广义极值分布的动态鲁棒性模型。为验证所提模型的有效性，以国内某区域枢纽机场142架航班为案例进行实验分析。实验结果表明：改进的BH-PSO算法较PSO算法在综合成本上降低8590.5元，降幅3.63%，收敛速度提升约50%。通过100组仿真场景验证，动态鲁棒性模型在成本增加0.62%~1.28%的前提下，冲突次数减少约20%，显著优于静态优化方案。相关研究结论一定程度缓解了传统模型的静态局限性，为智慧机场应对航班动态变化提供决策支持，对提升资源利用率和运营效率具有重要参考价值。

关键词: 航空运输, 停机位分配, 多目标优化, 航班时刻扰动, 粒子群算法, 鲁棒性

Abstract: Aiming at the tight gate resources and dynamic scheduling requirements in the context of the recovery of the civil aviation industry, a multi-objective optimization model for gate assignment integrating economy and robustness is proposed. First, a comprehensive economic objective function is constructed, which includes the costs of taxiing fuel consumption, gate service, and idle time. Then, a Backtracking-Hybrid Particle Swarm Optimization (BH-PSO) algorithm is proposed to alleviate the problem of traditional Particle Swarm Optimization (PSO) algorithm due to the excessive dependence of parameter initialization, and to enhance the global search ability. In addition, a dynamic robustness model based on the Generalized Extreme Value Distribution is further proposed for the uncertainty of flight schedules. To verify the effectiveness of the proposed model, an experimental analysis is conducted using a case of 142 flights at a regional hub airport in China. The experimental results show that the improved BH PSO algorithm reduces the comprehensive cost by 8590.5 yuan compared with the PSO algorithm, with a decrease of 3.63%, and the convergence speed is increased by about 50%. Through the verification of 100 simulation scenarios, the dynamic robustness model reduces the number of conflicts by about 20% on the premise of a cost increase of 0.62% to 1.28%, which is significantly better than the static optimization scheme. The relevant research conclusions alleviate the static limitations of traditional models to a certain extent, provide decision-making support for smart airports to deal with dynamic flight changes, and have important reference value for improving resource utilization and operational efficiency.

Key words: air transportation, gate assignment, multi-objective optimization, flight schedule perturbations, particle swarm optimization, robustness

中图分类号:

U8
V351.11

杜婧涵, 李佳祥, 程擎, 朱新平, 尹嘉男, 张魏宁. 融合经济性与鲁棒性的多目标停机位动态分配方法[J]. 交通运输系统工程与信息, 2025, 25(4): 326-336.

DU Jinghan, LI Jiaxiang, CHENG Qing, ZHU Xinping, YIN Jianan, ZHANG Weining. A Multi-objective Dynamic Gate Assignment Method Integrating Economy and Robustness[J]. Journal of Transportation Systems Engineering and Information Technology, 2025, 25(4): 326-336.

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http://www.tseit.org.cn/CN/Y2025/V25/I4/326

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融合经济性与鲁棒性的多目标停机位动态分配方法

A Multi-objective Dynamic Gate Assignment Method Integrating Economy and Robustness

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