交通运输系统工程与信息 ›› 2025, Vol. 25 ›› Issue (1): 250-257.DOI: 10.16097/j.cnki.1009-6744.2025.01.024

• 系统工程理论与方法 • 上一篇    下一篇

考虑效率和公平的飞机滑行路径双目标规划研究

张轮1,侯雪晶1,吴凌霄*2,徐博3   

  1. 1. 同济大学,道路与交通工程教育部重点实验室,上海201804;2.香港理工大学,航空及民航工程学系,香港999077;3. 上海理工大学,管理学院,上海200093
  • 收稿日期:2024-08-01 修回日期:2024-11-22 接受日期:2024-11-28 出版日期:2025-02-25 发布日期:2025-02-24
  • 作者简介:张轮(1970—),男,安徽滁州人,教授。
  • 基金资助:
    国家自然科学基金(U20A20330);国家重点研发计划(2022YFB2602200)。

ABi-objective Aircraft Taxiing Routing Planning Problem Considering Efficiency and Fairness

ZHANG Lun1, HOU Xuejing1, WU Lingxiao*2, XU Bo3   

  1. 1. The Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 201804, China; 2. The Department ofAeronautical andAviation Engineering, The Hong Kong Polytechnic University, Hong Kong 999077, China; 3. Business School, University of Shanghai for Science and Technology, Shanghai 200093, China
  • Received:2024-08-01 Revised:2024-11-22 Accepted:2024-11-28 Online:2025-02-25 Published:2025-02-24
  • Supported by:
    National Natural Science Foundation of China (U20A20330);National Key Research and Development Program of China (2022YFB2602200)。

摘要: 飞机滑行路径规划是机场交通管理的重要问题,需要同时考虑效率(设计系统最优的路径方案)和公平(为航空公司提供公平的服务)两项指标。基于此,本文研究双目标的飞机滑行路径规划问题,同时考虑效率和公平,并纳入飞机安全间隔时间和时间窗等影响因素。以最小化所有飞机的总延迟,以及最小化最大平均公平的公平偏差为目标,建立双目标混合整数非线性规划数学模型。根据该模型的特点,提出一个带有初始解算法加速策略的ε-约束方法求解,生成的解方案不需要决策者阐明对所考虑目标的特别偏好,而提供关于竞争目标之间存在的权衡信息。基于广东白云机场的场景进行数值实验,验证了模型和算法的适用性和有效性。实验结果表明:本文提出的带有初始解算法加速策略的ε-约束方法,相比经典ε-约束方法的求解速度更快,且随着飞机数量规模越大,加速时间越显著。在追求航空公司间的公平性时,会以牺牲效率为代价,而为了尽可能地保证机场运转的流畅性,在相对不繁忙的时间段调整飞机滑行路径方案是一种更优的选择。

关键词: 航空运输, 效率和公平, ε-约束方法, 飞机滑行, 路径规划, 碰撞冲突回避

Abstract: Aircraft taxiing routing planning is an important issue in airport traffic management, which requires the balance of efficiency (optimal routing for the airport system) and fairness (equitable service among airlines). This paper investigates a bi objective aircraft routing planning problem that incorporates both efficiency and fairness, along with considerations such as safety separation time between aircraft and time windows. The problem is formulated as a bi-objective mixed-integer nonlinear programming model, aimed at minimizing total aircraft delay and minimizing the maximum average fairness deviation among airlines. Given the characteristics of the model, an ε-constraint method coupled with an initial solution algorithm acceleration strategy, is proposed for the model solution. The generated solutions offer information into the trade-offs between the competing objectives without requiring decision-makers to articulate specific preferences. Numerical experiments based on Guangdong Baiyun Airport are conducted to validate the applicability and effectiveness of the model and algorithm. Results show that the proposed ε-constraint method, enhanced by the acceleration strategy, outperforms the classical ε-constraint method in solving the problems, with the acceleration becoming more pronounced as aircraft numbers increase. Achieving fairness among airlines often entails a sacrifice in efficiency, suggesting that taxiing routing adjustments should be made during less congested periods.

Key words: air transportation, efficiency and fairness, ε-constraint method, aircraft taxiing, routing planning, collision conflict avoidance

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