IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v648y2024ics0378437124003923.html
   My bibliography  Save this article

Flight delay propagation in the multiplex network system of airline networks

Author

Listed:
  • Zhang, Haoyu
  • Wu, Weiwei
  • Jiang, Yu
  • Chen, Xinyuan

Abstract

The flight delay propagation and recovery processes in airline networks differ due to differences in airline network structures, capacity distributions, and base airport locations. When each airline network is regarded as a network layer, flight delay propagation and interaction in a multiplex network system (MNS) composed of multiple airlines will become more complex and variable. In this paper, flight delays from different airlines are considered propagation sources, and an MNS-based flight delay propagation model is established under the framework of the susceptible-infected-susceptible model. By comparing the independent propagation process of delays in a single-layer airline network and the interactive propagation process of delays in an MNS, we investigate the impact of network structure on flight delays to propose corresponding delay control strategies for different airlines. The results show that unlike in single-layer networks, in an MNS, the behavior of airlines at an airport facilitates or inhibits delay propagation in other layers by influencing the network characteristics and propagation rate. The same airport may even play different roles in different layers, depending on the function it has. Therefore, not all flights are infected or have aggravated delays when accessing the MNS; instead, they are impacted by combined factors such as on-time performance, network structure, and flight interaction.

Suggested Citation

  • Zhang, Haoyu & Wu, Weiwei & Jiang, Yu & Chen, Xinyuan, 2024. "Flight delay propagation in the multiplex network system of airline networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 648(C).
  • Handle: RePEc:eee:phsmap:v:648:y:2024:i:c:s0378437124003923
    DOI: 10.1016/j.physa.2024.129883
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437124003923
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2024.129883?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Menno Yap & Oded Cats, 2021. "Predicting disruptions and their passenger delay impacts for public transport stops," Transportation, Springer, vol. 48(4), pages 1703-1731, August.
    2. Campanelli, Bruno & Fleurquin, Pablo & Arranz, Andrés & Etxebarria, Izaro & Ciruelos, Carla & Eguíluz, Víctor M. & Ramasco, José J., 2016. "Comparing the modeling of delay propagation in the US and European air traffic networks," Journal of Air Transport Management, Elsevier, vol. 56(PA), pages 12-18.
    3. Belkoura, Seddik & Cook, Andrew & Peña, José Maria & Zanin, Massimiliano, 2016. "On the multi-dimensionality and sampling of air transport networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 94(C), pages 95-109.
    4. Sismanidou, Athina & Tarradellas, Joan & Suau-Sanchez, Pere, 2022. "The uneven geography of US air traffic delays: Quantifying the impact of connecting passengers on delay propagation," Journal of Transport Geography, Elsevier, vol. 98(C).
    5. Chen, Shenwen & Du, Wenbo & Liu, Runran & Cao, Xianbin, 2023. "Finding spatial and temporal features of delay propagation via multi-layer networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 614(C).
    6. Woo, Young-Bin & Moon, Ilkyeong, 2021. "Scenario-based stochastic programming for an airline-driven flight rescheduling problem under ground delay programs," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 150(C).
    7. AhmadBeygi, Shervin & Cohn, Amy & Guan, Yihan & Belobaba, Peter, 2008. "Analysis of the potential for delay propagation in passenger airline networks," Journal of Air Transport Management, Elsevier, vol. 14(5), pages 221-236.
    8. Bombelli, Alessandro & Sallan, Jose Maria, 2023. "Analysis of the effect of extreme weather on the US domestic air network. A delay and cancellation propagation network approach," Journal of Transport Geography, Elsevier, vol. 107(C).
    9. Bolić, Tatjana & Castelli, Lorenzo & Corolli, Luca & Rigonat, Desirée, 2017. "Reducing ATFM delays through strategic flight planning," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 98(C), pages 42-59.
    10. Jianwei Wang & Jialu He & Wei Chen & Bo Xu, 2018. "Abnormal dynamics of cascading edge failures with congestion effect," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 29(10), pages 1-13, October.
    11. Hong, Chen & Zhang, Jun & Cao, Xian-Bin & Du, Wen-Bo, 2016. "Structural properties of the Chinese air transportation multilayer network," Chaos, Solitons & Fractals, Elsevier, vol. 86(C), pages 28-34.
    12. Baumgarten, Patrick & Malina, Robert & Lange, Anne, 2014. "The impact of hubbing concentration on flight delays within airline networks: An empirical analysis of the US domestic market," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 66(C), pages 103-114.
    13. Du, Wen-Bo & Zhang, Ming-Yuan & Zhang, Yu & Cao, Xian-Bin & Zhang, Jun, 2018. "Delay causality network in air transport systems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 466-476.
    14. Yu, Bin & Guo, Zhen & Asian, Sobhan & Wang, Huaizhu & Chen, Gang, 2019. "Flight delay prediction for commercial air transport: A deep learning approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 203-221.
    15. Zanin, Massimiliano, 2015. "Can we neglect the multi-layer structure of functional networks?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 430(C), pages 184-192.
    16. Kafle, Nabin & Zou, Bo, 2016. "Modeling flight delay propagation: A new analytical-econometric approach," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 520-542.
    17. Jiang, Yu & Xue, Qingwen & Wang, Yasha & Cai, Mengting & Zhang, Honghai & Li, Yahui, 2021. "Traffic congestion mechanism in mega-airport surface," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 577(C).
    18. Weiwei Wu & Haoyu Zhang & Tao Feng & Frank Witlox, 2019. "A Network Modelling Approach to Flight Delay Propagation: Some Empirical Evidence from China," Sustainability, MDPI, vol. 11(16), pages 1-16, August.
    19. Olivares, Felipe & Sun, Xiaoqian & Wandelt, Sebastian & Zanin, Massimiliano, 2023. "Measuring landing independence and interactions using statistical physics," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 170(C).
    20. Guo, Zhen & Hao, Mengyan & Yu, Bin & Yao, Baozhen, 2022. "Detecting delay propagation in regional air transport systems using convergent cross mapping and complex network theory," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Li, Chi & Mao, Jianfeng & Li, Lingyi & Wu, Jingxuan & Zhang, Lianmin & Zhu, Jianyu & Pan, Zibin, 2024. "Flight delay propagation modeling: Data, Methods, and Future opportunities," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 185(C).
    2. Chen, Shenwen & Du, Wenbo & Liu, Runran & Cao, Xianbin, 2023. "Finding spatial and temporal features of delay propagation via multi-layer networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 614(C).
    3. Bombelli, Alessandro & Sallan, Jose Maria, 2023. "Analysis of the effect of extreme weather on the US domestic air network. A delay and cancellation propagation network approach," Journal of Transport Geography, Elsevier, vol. 107(C).
    4. Guo, Zhen & Hao, Mengyan & Yu, Bin & Yao, Baozhen, 2022. "Detecting delay propagation in regional air transport systems using convergent cross mapping and complex network theory," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
    5. Li, Qiang & Wu, Lu & Guan, Xinjia & Tian, Ze-jin, 2024. "Interplay of network topologies in aviation delay propagation: A complex network and machine learning analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 638(C).
    6. Li, Qiang & Jing, Ranzhe, 2021. "Characterization of delay propagation in the air traffic network," Journal of Air Transport Management, Elsevier, vol. 94(C).
    7. Sismanidou, Athina & Tarradellas, Joan & Suau-Sanchez, Pere, 2022. "The uneven geography of US air traffic delays: Quantifying the impact of connecting passengers on delay propagation," Journal of Transport Geography, Elsevier, vol. 98(C).
    8. Kenan, Nabil & Jebali, Aida & Diabat, Ali, 2018. "The integrated aircraft routing problem with optional flights and delay considerations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 355-375.
    9. Chen, Gong & Fricke, Hartmut & Okhrin, Ostap & Rosenow, Judith, 2024. "Flight delay propagation inference in air transport networks using the multilayer perceptron," Journal of Air Transport Management, Elsevier, vol. 114(C).
    10. Kafle, Nabin & Zou, Bo, 2016. "Modeling flight delay propagation: A new analytical-econometric approach," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 520-542.
    11. Jingyi Qu & Shixing Wu & Jinjie Zhang, 2023. "Flight Delay Propagation Prediction Based on Deep Learning," Mathematics, MDPI, vol. 11(3), pages 1-24, January.
    12. Birolini, Sebastian & Jacquillat, Alexandre, 2023. "Day-ahead aircraft routing with data-driven primary delay predictions," European Journal of Operational Research, Elsevier, vol. 310(1), pages 379-396.
    13. Kim, Myeonghyeon & Park, Sunwook, 2021. "Airport and route classification by modelling flight delay propagation," Journal of Air Transport Management, Elsevier, vol. 93(C).
    14. Wang, Yanjun & Li, Max Z. & Gopalakrishnan, Karthik & Liu, Tongdan, 2022. "Timescales of delay propagation in airport networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 161(C).
    15. Sajjad Aslani Khiavi & Farzad Hashemzadeh & Hamid Khaloozadeh, 2024. "Modeling and adaptive control of demand oscillation propagation in an uncertain aerial transportation network," OPSEARCH, Springer;Operational Research Society of India, vol. 61(3), pages 1383-1403, September.
    16. Tan, Xinlong & Jia, Rongwen & Yan, Jia & Wang, Kun & Bian, Lei, 2021. "An Exploratory analysis of flight delay propagation in China," Journal of Air Transport Management, Elsevier, vol. 92(C).
    17. Du, Wen-Bo & Zhang, Ming-Yuan & Zhang, Yu & Cao, Xian-Bin & Zhang, Jun, 2018. "Delay causality network in air transport systems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 466-476.
    18. Li, Max Z. & Ryerson, Megan S. & Balakrishnan, Hamsa, 2019. "Topological data analysis for aviation applications," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 128(C), pages 149-174.
    19. Hu, Yue & Dai, Liang & Fuellhart, Kurt & Witlox, Frank, 2024. "Examining competition among airline regarding route portfolios at domestic hubs under government regulation: The case of China's aviation market," Journal of Air Transport Management, Elsevier, vol. 116(C).
    20. Zhe Zheng & Wenbin Wei & Bo Zou & Minghua Hu, 2020. "How Late Does Your Flight Depart? A Quantile Regression Approach for a Chinese Case Study," Sustainability, MDPI, vol. 12(24), pages 1-16, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:648:y:2024:i:c:s0378437124003923. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.