IDEAS home Printed from https://ideas.repec.org/a/eee/jaitra/v23y2012icp1-4.html
   My bibliography  Save this article

Parameterized framework for the analysis of probabilities of aircraft delay at an airport

Author

Listed:
  • Wesonga, Ronald
  • Nabugoomu, Fabian
  • Jehopio, Peter

Abstract

The study analyses ground delays and air holding at Entebbe International Airport over five years. Daily probabilities for aircraft departure and arrival delays at are generated for each. The mean probabilities of delay for ground delays and air holding at 50% delay threshold levels are 0.94 and 0.82 that fall to 0.49 and 0.36 when 60% delay threshold levels are used. Simulations are performance for delay threshold levels to monitor for the trends of the daily probabilities for the study period. The general conclusion is that a parameter-based framework is best suited to determine the probability of aircraft delay at an airport.

Suggested Citation

  • Wesonga, Ronald & Nabugoomu, Fabian & Jehopio, Peter, 2012. "Parameterized framework for the analysis of probabilities of aircraft delay at an airport," Journal of Air Transport Management, Elsevier, vol. 23(C), pages 1-4.
    • Handle: RePEc:eee:jaitra:v:23:y:2012:i:c:p:1-4
    DOI: 10.1016/j.jairtraman.2012.02.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0969699712000555
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jairtraman.2012.02.001?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. Tu, Yufeng & Ball, Michael O. & Jank, Wolfgang S., 2008. "Estimating Flight Departure Delay DistributionsA Statistical Approach With Long-Term Trend and Short-Term Pattern," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 112-125, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wesonga, Ronald, 2015. "Airport utility stochastic optimization models for air traffic flow management," European Journal of Operational Research, Elsevier, vol. 242(3), pages 999-1007.
    2. de Oliveira, McWillian & Eufrásio, Ana Beatriz Rebouças & Guterres, Marcelo Xavier & Murça, Mayara Condé Rocha & Gomes, Rogéria de Arantes, 2021. "Analysis of airport weather impact on on-time performance of arrival flights for the Brazilian domestic air transportation system," Journal of Air Transport Management, Elsevier, vol. 91(C).
    3. 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.
    4. Kim, Myeonghyeon & Park, Sunwook, 2021. "Airport and route classification by modelling flight delay propagation," Journal of Air Transport Management, Elsevier, vol. 93(C).

    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. Chandra, Aitichya & Verma, Ashish & Sooraj, K.P. & Padhi, Radhakant, 2023. "Modelling and assessment of the arrival and departure process at the terminal area: A case study of Chennai international airport," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 615(C).
    2. Pedro Jose Gudiel Pineda & Chao-Che Hsu & James J. H. Liou & Huai-Wei Lo, 2018. "A Hybrid Model for Aircraft Type Determination Following Flight Cancellation," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 17(04), pages 1147-1172, July.
    3. Kim, Myeonghyeon & Bae, Jiheon, 2021. "Modeling the flight departure delay using survival analysis in South Korea," Journal of Air Transport Management, Elsevier, vol. 91(C).
    4. Mariana Nicolae & Mazhar Arıkan & Vinayak Deshpande & Mark Ferguson, 2017. "Do Bags Fly Free? An Empirical Analysis of the Operational Implications of Airline Baggage Fees," Management Science, INFORMS, vol. 63(10), pages 3187-3206, October.
    5. 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.
    6. Michelle Dunbar & Gary Froyland & Cheng-Lung Wu, 2012. "Robust Airline Schedule Planning: Minimizing Propagated Delay in an Integrated Routing and Crewing Framework," Transportation Science, INFORMS, vol. 46(2), pages 204-216, May.
    7. Mazhar Arıkan & Vinayak Deshpande & Milind Sohoni, 2013. "Building Reliable Air-Travel Infrastructure Using Empirical Data and Stochastic Models of Airline Networks," Operations Research, INFORMS, vol. 61(1), pages 45-64, February.
    8. 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.
    9. Azadian, Farshid & Murat, Alper E. & Chinnam, Ratna Babu, 2012. "Dynamic routing of time-sensitive air cargo using real-time information," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(1), pages 355-372.
    10. Sai Ho Chung & Hoi Lam Ma & Hing Kai Chan, 2017. "Cascading Delay Risk of Airline Workforce Deployments with Crew Pairing and Schedule Optimization," Risk Analysis, John Wiley & Sons, vol. 37(8), pages 1443-1458, August.
    11. Truong, Thuan V., 2011. "The Distribution Function of Airport Taxi‐Out Times and Selected Applications," Journal of the Transportation Research Forum, Transportation Research Forum, vol. 50(2).
    12. Diana, Tony, 2018. "Can machines learn how to forecast taxi-out time? A comparison of predictive models applied to the case of Seattle/Tacoma International Airport," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 119(C), pages 149-164.
    13. Michael Redmond & Ann Melissa Campbell & Jan Fabian Ehmke, 2020. "Data-driven planning of reliable itineraries in multi-modal transit networks," Public Transport, Springer, vol. 12(1), pages 171-205, March.
    14. Sternberg, Alice & Carvalho, Diego & Murta, Leonardo & Soares, Jorge & Ogasawara, Eduardo, 2016. "An analysis of Brazilian flight delays based on frequent patterns," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 95(C), pages 282-298.
    15. Gwiggner, Claus & Nagaoka, Sakae, 2014. "Data and queueing analysis of a Japanese air-traffic flow," European Journal of Operational Research, Elsevier, vol. 235(1), pages 265-275.
    16. Mai, Feng & Fry, Michael J. & Ohlmann, Jeffrey W., 2018. "Model-based capacitated clustering with posterior regularization," European Journal of Operational Research, Elsevier, vol. 271(2), pages 594-605.
    17. Wang, Chunzheng & Hu, Minghua & Yang, Lei & Zhao, Zheng, 2022. "Improving the spatial-temporal generalization of flight block time prediction: A development of stacking models," Journal of Air Transport Management, Elsevier, vol. 103(C).
    18. Lambelho, Miguel & Mitici, Mihaela & Pickup, Simon & Marsden, Alan, 2020. "Assessing strategic flight schedules at an airport using machine learning-based flight delay and cancellation predictions," Journal of Air Transport Management, Elsevier, vol. 82(C).
    19. 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.
    20. Khan, Waqar Ahmed & Chung, Sai-Ho & Eltoukhy, Abdelrahman E.E. & Khurshid, Faisal, 2024. "A novel parallel series data-driven model for IATA-coded flight delays prediction and features analysis," Journal of Air Transport Management, Elsevier, vol. 114(C).

    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:jaitra:v:23:y:2012:i:c:p:1-4. 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/journal-of-air-transport-management/ .

    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.