Journal of Air Transport Management最新文献_第8页

Integrated hub airport location and fleets planning for airline-alliance-oriented freight transport system 以航空联盟为导向的货运系统的综合枢纽机场定位和机队规划

IF 3.6 2区工程技术 Q2 TRANSPORTATION

Journal of Air Transport Management

Pub Date : 2026-01-01 Epub Date: 2025-08-26 DOI: 10.1016/j.jairtraman.2025.102889

Yu Zheng , Yi Huang , Hua Wang

The rapid growth of e-commerce has led to a surge in air cargo demand. Rather than operating independently, airlines are increasingly collaborating to capture a larger market share. This study investigates the integrated hub airport location and fleet planning problem under the context of airline alliances to enhance sustainable urban freight transportation. Three optimization models are proposed in different airline cooperation modes: i) model INDHL-INDFP, where airlines independently determine hub airport locations and fleet planning, ii) model INTHL-INDFP, where airlines collaboratively decide hub airport locations while planning fleets individually based on their cargo demand, and iii) model INTHLFP, where airlines make integrated decisions on both hub locations and fleet planning. These models are applied to networks of varying scales, and their performance is compared. Results indicate that integrated decision-making within airline alliances effectively reduces total system costs, with cost-saving benefits becoming more pronounced as network size increases. Additionally, this approach aligns freighter capacity with cargo demand, enhancing system resilience to demand fluctuations. Sensitivity analysis further reveals that the optimal number of hub airports depends on network scale and varies under different airline cooperation strategies. Moreover, network size significantly influences the determination of the maximum number of flights connected to other hubs for a hub. This study provides valuable insights into optimizing airline cooperation strategies to improve efficiency and sustainability in air cargo transportation.

电子商务的快速发展导致航空货运需求激增。航空公司不再独立运营，而是越来越多地合作以获取更大的市场份额。本研究探讨航空联盟背景下的枢纽机场选址与机队规划问题，以提升城市货运的永续性。针对不同的航空公司合作模式，提出了三种优化模型：1)航空公司独立决定枢纽机场位置和机队规划的INDHL-INDFP模型；2)航空公司根据货运需求单独规划机队，协同决定枢纽机场位置的INTHL-INDFP模型；3)航空公司对枢纽机场位置和机队规划进行综合决策的INTHLFP模型。将这些模型应用于不同规模的网络，并比较了它们的性能。结果表明，航空公司联盟内部的综合决策有效地降低了系统总成本，随着网络规模的增加，成本节约的好处变得更加明显。此外，这种方法使货运能力与货物需求保持一致，增强了系统对需求波动的弹性。敏感度分析进一步表明，枢纽机场的最优数量取决于网络规模，在不同的航空公司合作策略下也有所不同。此外，网络规模显著影响一个枢纽连接到其他枢纽的最大航班数量的确定。本研究为优化航空公司合作策略以提高航空货运的效率和可持续性提供了有价值的见解。

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引用次数: 0

Electric and fuel aircraft schedule optimizing problem with battery charging and swapping — The case of flight in china 基于电池充电和更换的电动和燃油飞机调度优化问题——以中国航班为例

IF 3.6 2区工程技术 Q2 TRANSPORTATION

Journal of Air Transport Management

Pub Date : 2026-01-01 Epub Date: 2025-09-03 DOI: 10.1016/j.jairtraman.2025.102890

Yuxiang Tang, Li Wang, Wenxuan Kang, Wenchao Liu, Yufeng Zhuang

Under the trend of electrification, civil aviation is promoting electric aircraft to reduce emissions. In recent years, technological advancements have opened up the possibility of employing electric aircraft in flight routes. This paper will explore the scheduling problem of electric and fuel aircraft. The mixed operation mode of electric and fuel aircraft is necessary in the current state of green development since electric aircraft currently face significant challenges for operators of long haul routes. Meanwhile, the battery swapping technology can significantly reduce aircraft charging time at airports. Therefore, this paper investigates the optimization problem of the electric and fuel aircraft schedule with battery charging and swapping (ef-ASOP). We introduce a mixed integer programming formulation for the ef-ASOP to minimize total emission, charging, swapping and delay costs. The constraints of the model consider flow, charging and time constraints. We propose M-parameters bounds and two valid inequalities for model enhancement. The Air China case study demonstrates practical insights. The results show that an increase in the number of electric aircraft and battery capacity leads to a reduction in emission costs and an increase in delay costs. Electric aircraft and fuel aircraft are complementary. Some long haul routes cannot be operated by electric aircraft, but can be met by fuel aircraft. At the same time, fuel aircraft also help reduce delay costs. Meanwhile, more widespread deployment of battery swapping stations can reduce delays and improve passenger satisfaction.

在电气化的趋势下，民航正在推广电动飞机，以减少排放。近年来，技术进步为在航线上使用电动飞机提供了可能性。本文将探讨电动飞机和燃油飞机的调度问题。在当前绿色发展的状态下，电动飞机和燃油飞机的混合运营模式是必要的，因为电动飞机目前面临着长途航线运营商的重大挑战。同时，电池交换技术可以显著缩短飞机在机场的充电时间。为此，本文研究了考虑电池充电和换电的燃油飞机调度优化问题。为了使总排放、充电、交换和延迟成本最小化，我们引入了一个混合整数规划公式。模型的约束考虑了流量、充电和时间约束。我们提出了m参数边界和两个有效的模型增强不等式。国航的案例研究展示了实际的见解。结果表明，电动飞机数量和电池容量的增加导致排放成本的降低和延误成本的增加。电动飞机和燃油飞机是互补的。有些长途航线不能由电动飞机执飞，但可以由燃油飞机执飞。同时，燃油飞机也有助于降低延误成本。同时，更广泛地部署电池更换站可以减少延误，提高乘客满意度。

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引用次数: 0

Applying Large Language Models to investigate how people with disabilities interact at airports 应用大型语言模型来调查残疾人如何在机场互动

IF 3.6 2区工程技术 Q2 TRANSPORTATION

Journal of Air Transport Management

Pub Date : 2026-01-01 Epub Date: 2025-08-30 DOI: 10.1016/j.jairtraman.2025.102880

Steven Tanner McCullough , Ariana Grant , Evan Mistur , June Young Park

Rapid transition in social and environmental conditions consistently demand changes in how airport facilities are operated and managed, creating an ongoing stream of new and unique barriers to accessibility. In this paper, a novel framework in conjunction with Large Language Model (LLM) and accessibility design standards is used to discover the perceived accessibility of people with disability (PWD) in airports, mined from location-based social media reviews. The analysis uncovered key insights into how different airports perform in terms of accessibility among 64 hub airports in the United States. While some airports excel in most areas that are legislated by the Americans with Disabilities Act (ADA), others face challenges in providing consistent and inclusive experiences. Primarily, the initial arrival experiences at airports are seen as the most significant factor influencing PWD overall perceptions of accessibility throughout the entire airport, highlighting the importance of consistent and effective first contact in shaping the journey of PWD.

社会和环境条件的快速变化不断要求机场设施的运营和管理方式发生变化，从而不断产生新的和独特的无障碍障碍。本文结合大语言模型（Large Language Model， LLM）和无障碍设计标准，从基于位置的社交媒体评论中挖掘机场残障人士（PWD）的无障碍感知。该分析揭示了美国64个枢纽机场在可达性方面的不同机场表现的关键见解。虽然一些机场在《美国残疾人法案》（ADA）规定的大多数领域表现出色，但其他机场在提供一致和包容的体验方面面临挑战。首先，首次抵达机场的体验被视为影响残疾人士对整个机场无障碍程度的整体看法的最重要因素，这突显了始终如一和有效的首次接触对残疾人士旅程的重要性。

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引用次数: 0

Technological progress and biases in airline productivity: A network MPI analysis under external disruptions 技术进步与航空公司生产力偏差：外部干扰下的网络MPI分析

IF 3.6 2区工程技术 Q2 TRANSPORTATION

Journal of Air Transport Management

Pub Date : 2026-01-01 Epub Date: 2025-09-03 DOI: 10.1016/j.jairtraman.2025.102892

Ming-Miin Yu , Li-Hsueh Chen

This study aims to investigate the significant role of technological progress and its biases among different factors and outputs within a two-stage network production technology structure in influencing productivity changes in airlines. To address variations in productivity under external disruptions and market fluctuations, this study develops a novel network Malmquist Productivity Index (MPI) decomposition model, identifying both inter-group biases between inputs and outputs and intra-group biases among input factors and outputs. Analyzing data from 2015 to 2021 for 16 global airlines, the study measures productivity changes and their components within the network production framework. The technological change is decomposed to analyze the bias characteristics of input factors such as labor and operational expenses, intermediate products like available seat kilometers and available freight ton kilometers, and output factors including revenue passenger kilometers and revenue freight ton kilometers. The findings indicate that efficiency improvements and technological progress are primary drivers of productivity growth, while output-biased technological change limits this growth. Efficiency improvements, increased magnitude of technological change, and input-biased technological change in the service stage contribute to overall productivity gains, mitigating the negative impact of efficiency deterioration and reduced technological change in the production stage. Notably, productivity regressed during 2020–2021, reflecting operational disruptions caused by external shocks such as the COVID-19 pandemic. These results suggest that targeted technological advancements and efficiency improvements in specific production and service stages can significantly influence overall productivity. The study provides strategic insights for airlines to navigate disruptions, emphasizing the importance of understanding and managing technological biases to enhance productivity.

本研究旨在探讨两阶段网络生产技术结构中技术进步及其在不同要素和产出之间的偏差对航空公司生产率变化的显著影响。为了解决外部干扰和市场波动下的生产率变化，本研究开发了一种新的网络Malmquist生产率指数（MPI）分解模型，识别了投入和产出之间的群体间偏差以及投入因素和产出之间的群体内偏差。该研究分析了2015年至2021年全球16家航空公司的数据，衡量了网络生产框架内的生产力变化及其组成部分。对技术变革进行分解，分析劳动力和运营费用等投入因素、可用座位公里数和可用货运吨公里等中间产品、收入客运公里数和收入货运吨公里等产出因素的偏差特征。研究结果表明，效率提高和技术进步是生产率增长的主要驱动力，而偏向于产出的技术变革限制了这种增长。服务阶段的效率提高、技术变化幅度增加和投入偏向的技术变化有助于整体生产率的提高，减轻了生产阶段效率恶化和技术变化减少的负面影响。值得注意的是，由于COVID-19大流行等外部冲击造成的运营中断，2020-2021年期间生产率出现回落。这些结果表明，在特定的生产和服务阶段，有针对性的技术进步和效率提高可以显著影响整体生产率。该研究为航空公司提供了应对干扰的战略见解，强调了理解和管理技术偏差对提高生产力的重要性。

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引用次数: 0

The reciprocal impact between air passenger transport and international tourism in Singapore 航空客运与新加坡国际旅游业的相互影响

IF 3.6 2区工程技术 Q2 TRANSPORTATION

Journal of Air Transport Management

Pub Date : 2025-11-01 Epub Date: 2025-08-05 DOI: 10.1016/j.jairtraman.2025.102877

Quang Hai Nguyen

This study examines the interplay between air passenger transport and international tourism through the role of GDP (Gross Domestic Product) and trade openness in 11 key markets of Singapore. Co-integration tests indicate that although air passenger transport and international tourism may not be individually stable in some markets, their fluctuations are strongly and durably related. The estimation results using a combined SARIMA (Seasonal Autoregressive Integrated Moving Average), X (exogenous factors), and GARCH (Generalized Autoregressive Conditional Heteroskedasticity) model show that there is a strong interrelationship between air passenger transport and the number of international tourists to Singapore, but air passenger transport is less sensitive to fluctuations in the number of international tourists. GDP and trade openness also have significant impacts on the demand for both sectors, but at different levels across markets. The cyclical, seasonal, and external shock effects found in air passenger transport and international tourism indicate the diversity in behavior and characteristics of each market. The research results provide a basis for managers and policymakers to forecast and formulate development policies for tourism and air transport.

本研究通过国内生产总值（GDP）和新加坡11个主要市场的贸易开放程度，考察了航空客运与国际旅游业之间的相互作用。协整检验表明，虽然航空客运和国际旅游业在某些市场中可能不是单独稳定的，但它们的波动是强烈而持久的相关。使用SARIMA（季节性自回归综合移动平均）、X（外生因子）和GARCH（广义自回归条件异方差）模型的组合估计结果表明，航空客运与新加坡国际游客数量之间存在很强的相互关系，但航空客运对国际游客数量的波动不太敏感。GDP和贸易开放度对这两个部门的需求也有显著影响，但不同市场的影响程度不同。在航空客运和国际旅游中发现的周期性、季节性和外部冲击效应表明每个市场的行为和特征的多样性。研究结果为管理者和决策者预测和制定旅游和航空运输发展政策提供了依据。

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引用次数: 0

Profit Efficiency: Insight into airline business models and strategic choices 利润效率：洞察航空公司的商业模式和战略选择

IF 3.9 2区工程技术 Q2 TRANSPORTATION

Journal of Air Transport Management

Pub Date : 2025-11-01 Epub Date: 2025-07-22 DOI: 10.1016/j.jairtraman.2025.102863

Fecri Karanki , Roger Schaufele

Following a challenging start to the 21st century, airlines rebounded to achieve record profits in the aftermath of the Great Recession (2007–2009). While profitability refers to the absolute financial gains of a firm, profit efficiency is a measure of how effectively a firm converts its resources into maximum potential profit, given its operating environment and input prices. These distinct economic concepts raise key questions about airline strategies: Can airlines maximize their profits? Which business models achieve higher profit efficiency? What factors influence their profit efficiency? This study addresses these questions using a stochastic profit efficiency model based on data from U.S. airlines spanning from 2009 to 2019. Our findings reveal that the U.S. airline industry exhibits an average profit efficiency of 93.2 %. Low-Cost Carriers (LCCs) have a higher mean efficiency score of 98.7 % while Full-Service Airlines (FSAs) follow them with 95.3 %. Ultra-Low-Cost Carriers (ULCCs) have the lowest profit efficiency at 86.1 %. Finally, LCCs have demonstrated more stable profit efficiency over the years. In addition, ancillary revenues positively impact the profit efficiency, indicating higher markup resulting from add-on pricing. The strategies implemented after the Great Recession—such as capacity discipline and mergers—have significantly increased profit efficiency while the airport network expansion result in lower profit inefficiency. Overall, this study highlights the extent of profit efficiency for the U.S. airline industry and identifies the key factors influencing it.

在经历了21世纪充满挑战的开端之后，航空公司在经济大衰退（2007-2009）之后反弹，实现了创纪录的利润。盈利能力是指企业的绝对财务收益，而利润效率是衡量企业在其经营环境和投入价格的情况下，如何有效地将其资源转化为最大潜在利润。这些截然不同的经济概念提出了有关航空公司战略的关键问题：航空公司能否实现利润最大化？哪种商业模式的利润效率更高？影响他们利润效率的因素是什么？本研究使用基于2009年至2019年美国航空公司数据的随机利润效率模型来解决这些问题。我们的研究结果显示，美国航空业的平均利润效率为93.2%。低成本航空公司（lcc）的平均效率得分更高，为98.7%，而全服务航空公司（FSAs）的平均效率得分为95.3%。超低成本航空公司（ulcc）的利润效率最低，为86.1%。最后，低成本航空公司多年来表现出更稳定的利润效率。此外，辅助收入正向影响利润效率，表明附加定价导致更高的加价。经济大衰退后实施的运力约束和合并等战略显著提高了利润效率，而机场网络扩张则降低了利润效率。总体而言，本研究突出了美国航空业的利润效率程度，并确定了影响它的关键因素。

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引用次数: 0

Multi-agent task allocation and path planning for autonomous ground support equipment 自主地面保障设备多智能体任务分配与路径规划

IF 3.9 2区工程技术 Q2 TRANSPORTATION

Journal of Air Transport Management

Pub Date : 2025-11-01 Epub Date: 2025-07-18 DOI: 10.1016/j.jairtraman.2025.102855

Manouk van der Zwan , Gülçin Ermiş, Alexei Sharpanskykh

We aim to contribute to the automation of ground handling tasks using autonomous ground support equipment (GSE) at airports. Automation of airside operations has recently become critical for the airports to achieve higher levels of safety and efficiency under growing traffic demand and requires solving a complex scheduling and path planning problem. To address this problem, we present a multi-agent task allocation and path planning model for handling airside operations on the apron. In the problem, the ground handling tasks are to be allocated to the equipment, the trips of vehicles should be scheduled within specific time windows considering the flight schedules, and the collisions of vehicles on the apron and service roads should be avoided. We present a centralized multi-agent task allocation and routing model which aims to optimize the allocation and routing of various types of ground handling tasks over a heterogeneous set of GSE vehicles. We convert the allocation and routing problem into vehicle routing problem with time windows, pick-ups, deliveries and solve the problem using a warm start mixed integer linear programming (MILP) model. We also introduce a nonlinear objective function which converts the MILP model into a mixed integer nonlinear programming (MINLP) model, to minimize the time service locations at the stands are occupied. Then, we solve the corresponding path finding problem to find collision free paths for the GSE, by the multi-agent path finding model. The proposed model outperforms the decentralized approach in previous research regarding the allocation rate of assigning tasks to vehicles and the performance indicators of finding conflict free paths, and in CPU time. The mean deviations from shortest paths were considerably small in path planning which means that the solution quality was high. Furthermore, the CPU time of allocating tasks has been reduced by 48% compared to the CPU time of decentralized allocation.

我们的目标是利用机场的自主地面支持设备（GSE）为地面处理任务的自动化做出贡献。在日益增长的交通需求下，空侧操作自动化对机场实现更高水平的安全和效率至关重要，需要解决复杂的调度和路径规划问题。为了解决这个问题，我们提出了一个多智能体任务分配和路径规划模型来处理停机坪上的空侧操作。在问题中，将地面服务任务分配给设备，考虑航班时刻表，在特定的时间窗口内安排车辆的行程，避免停机坪与服务道路上车辆的碰撞。我们提出了一个集中的多智能体任务分配和路由模型，该模型旨在优化异构GSE车辆上各种类型地勤任务的分配和路由。我们将分配和路径问题转化为有时间窗的车辆路径问题，采用热启动混合整数线性规划（MILP）模型求解。同时引入非线性目标函数，将MILP模型转化为混合整数非线性规划（MINLP）模型，使服务点占用时间最小化。然后，通过多智能体寻路模型，解决相应的寻路问题，为GSE寻找无碰撞路径。在任务分配率、寻找无冲突路径的性能指标和CPU时间方面，该模型优于以往研究中的分散方法。在路径规划中，与最短路径的平均偏差相当小，这意味着解决方案的质量很高。此外，分配任务的CPU时间比分散分配的CPU时间减少了48%。

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引用次数: 0

Passenger perceptions of Artificial Intelligence in airline operations: Implications for air transport management 乘客对航空公司运营中人工智能的看法：对航空运输管理的影响

IF 3.6 2区工程技术 Q2 TRANSPORTATION

Journal of Air Transport Management

Pub Date : 2025-11-01 Epub Date: 2025-07-31 DOI: 10.1016/j.jairtraman.2025.102874

Joan-Francesc Fondevila-Gascón , Óscar Gutiérrez-Aragón , David Lopez-Lopez , Gonzalo Curiel-Barrios , Júlia Alabart-Algueró

Artificial Intelligence (AI) is reshaping the aviation industry, driving efficiency, automation, and innovation across multiple operational domains. This study examines commercial airline passengers’ perceptions of AI’s role in addressing key industry challenges, including air traffic management, predictive maintenance, passenger experience, and sustainability. Using a quantitative approach, a survey was conducted among 320 airline passengers in Spain to assess their attitudes toward AI-driven applications in aviation. The findings reveal strong support for AI in optimizing flight operations, reducing delays, and enhancing security procedures. However, significant skepticism remains regarding AI’s autonomy in decision-making, particularly in pilot replacement and automated flight rerouting. Statistical analyses indicate that younger and frequent travelers exhibit higher confidence in AI’s potential, whereas older passengers demonstrate greater reluctance toward AI-driven automation. Additionally, AI is perceived as a crucial enabler of environmental sustainability, with respondents acknowledging its role in reducing fuel consumption and emissions. These insights provide valuable implications for policymakers, airlines, and technology developers seeking to align AI adoption with passenger expectations while ensuring safety, efficiency, and regulatory compliance. The study highlights the need for a balanced approach that integrates AI’s technological advancements with human oversight to foster trust and acceptance in the future of AI-powered aviation.

人工智能（AI）正在重塑航空业，推动多个运营领域的效率、自动化和创新。本研究调查了商业航空公司乘客对人工智能在解决关键行业挑战方面的作用的看法，包括空中交通管理、预测性维护、乘客体验和可持续性。采用定量方法，对西班牙320名航空公司乘客进行了一项调查，以评估他们对航空领域人工智能应用的态度。研究结果显示，人工智能在优化航班运营、减少延误和加强安全程序方面得到了强有力的支持。然而，对于人工智能在决策方面的自主性，特别是在飞行员替换和自动飞行改道方面，仍然存在很大的怀疑。统计分析表明，年轻和经常旅行的人对人工智能的潜力更有信心，而年长的乘客对人工智能驱动的自动化表现出更大的不情愿。此外，人工智能被认为是环境可持续性的关键推动者，受访者承认其在减少燃料消耗和排放方面的作用。这些见解为政策制定者、航空公司和技术开发人员提供了有价值的建议，他们希望将人工智能的采用与乘客的期望结合起来，同时确保安全、效率和法规遵从性。该研究强调，需要采取一种平衡的方法，将人工智能的技术进步与人类的监督相结合，以促进对人工智能航空未来的信任和接受。

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引用次数: 0

The impacts of airport economic zones on local urban development in China 中国空港经济区对地方城市发展的影响

IF 3.6 2区工程技术 Q2 TRANSPORTATION

Journal of Air Transport Management

Pub Date : 2025-11-01 Epub Date: 2025-08-05 DOI: 10.1016/j.jairtraman.2025.102875

Jianhua Pi , Xingjian Liu , Will W. Qiang , Chris Webster

China's implementation of Airport Economic Zones (AEZs) seeks to capitalize on aviation infrastructure for local development. While existing studies have assessed airport-related urban development in China, the specific impacts of AEZ policies on local economies remain underexamined. To this end, our study evaluates the impacts of AEZs on local economies, utilizing a panel dataset of 62 prefecture-level cities in China spanning 2000–2019. We employ a heterogeneous timing difference-in-differences method to assess localized economic impacts of AEZs, considering three specific treatment timings. The results show that AEZs have positive but limited impacts on localized economic growth, particularly evident in increased economic activities around airports. Local economic impacts of more recently announced national airport economic demonstration zones are insignificant in the analysis. Meanwhile, the establishment of other kinds of development zones around airports fosters nearby economic activity and employment in airport-related sectors, oftentimes with higher levels of statistical significance. These findings add empirical evidence for airport region development's impact on economy and underscore the importance of institutional support for maximizing AEZs' contributions to urban development.

中国实施空港经济区（aez）旨在利用航空基础设施促进地方发展。虽然现有的研究已经评估了中国与机场相关的城市发展，但经济特区政策对当地经济的具体影响仍未得到充分研究。为此，本研究利用2000-2019年中国62个地级市的面板数据集，评估了经济特区对地方经济的影响。考虑到三种特定的治疗时机，我们采用了一种异质时间差中差的方法来评估aez的局部经济影响。结果表明，经济特区对地区经济增长的影响是积极但有限的，特别是在机场周边经济活动增加方面。在分析中，最近公布的国家空港经济示范区对地方经济的影响不显著。与此同时，在机场周围建立其他类型的开发区会促进附近与机场相关部门的经济活动和就业，通常具有更高的统计显著性。这些发现为空港区发展对经济的影响提供了经验证据，并强调了制度支持对于最大限度地发挥空港区对城市发展的贡献的重要性。

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引用次数: 0

Time series prediction of airport operational resilience under severe weather conditions 恶劣天气条件下机场运行弹性的时间序列预测

IF 3.6 2区工程技术 Q2 TRANSPORTATION

Journal of Air Transport Management

Pub Date : 2025-11-01 Epub Date: 2025-07-31 DOI: 10.1016/j.jairtraman.2025.102862

Yuhui Zhang , Lili Liu , Xiong Peng

Airport operational resilience is a crucial metric reflecting an airport’s capacity to adapt to external shocks, essential for maintaining safety and operational efficiency. While there has been research on airport resilience under various severe weather conditions, the specific contributing factors and their impacts remain inadequately explored. This study develops a comprehensive index system that integrates airport performance and meteorological data, using a random forest algorithm to quantify the influence of various factors on airport resilience across five types of severe weather. Furthermore, a PatchTST(Patch time series Transformer)-based time series model improved by the Cauchy loss function is proposed to accurately predict airport operational resilience. Focusing on severe weather events during the period from January 2023 to July 2024 at Dallas-Fort Worth International Airport in the United States. To mitigate multicollinearity, variables with high Pearson correlation and variance inflation factor (VIF) values were removed prior to analysis. Feature importance results reveal that hourly flight movements (HFM) consistently hold the highest importance across weather types, while temperature (TEMP), relative humidity (RHUM) and air pressure (PRES) exhibit relatively higher meteorological influence despite limited overall impact. The optimal Cauchy-PatchTST model, with a look-back window of

L = 36

and a forecast length of

T = 1

, outperforms the traditional PatchTST model with MSE loss, three Transformer-based models and other optimized machine learning algorithms, achieving a 15.49% to 94.10% reduction in MAE on the test set. This study provides critical indicator analysis for airports across various severe weather conditions and offers reliable resilience data to support future operations management.

机场运营弹性是反映机场适应外部冲击能力的关键指标，对保持安全和运营效率至关重要。虽然对各种恶劣天气条件下的机场弹性进行了研究，但具体的影响因素及其影响仍未得到充分探讨。本研究开发了一个综合指标体系，将机场性能和气象数据整合在一起，使用随机森林算法量化各种因素对五种类型恶劣天气下机场恢复力的影响。在此基础上，提出了一种基于Patch时间序列变压器（Patch time series Transformer）的时间序列模型，并对其进行了柯西损失函数的改进，以准确预测机场运行弹性。重点关注2023年1月至2024年7月期间在美国达拉斯-沃斯堡国际机场发生的恶劣天气事件。为了减轻多重共线性，在分析之前去除具有高Pearson相关性和方差膨胀因子（VIF）值的变量。特征重要性结果显示，每小时飞行运动（HFM）在各种天气类型中始终保持最高的重要性，而温度（TEMP）、相对湿度（RHUM）和气压（PRES）表现出相对较高的气象影响，尽管总体影响有限。最优Cauchy-PatchTST模型的回溯窗口为L=36，预测长度为T=1，优于传统的带有MSE损失的PatchTST模型、基于三个变压器的模型以及其他优化的机器学习算法，在测试集上MAE降低了15.49% ~ 94.10%。该研究为各种恶劣天气条件下的机场提供了关键指标分析，并提供了可靠的弹性数据，以支持未来的运营管理。

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引用次数: 0