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Enhanced delay propagation tree model with Bayesian Network for modelling flight delay propagation

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  • Weiwei Wu
  • Cheng-Lung Wu

Abstract

An enhanced Delay Propagation Tree model with Bayesian Network (DPT-BN) is developed to model multi-flight delay propagation and delay interdependencies. Using a set of real airline data, results show that flights have non-homogeneous delay propagation effects. The DPT-BN model is used to infer posterior delay profiles with different delay and scheduling scenarios. The major contribution of the DPT-BN model is to demonstrate how the modelling of non-independent and identically distributed delay profiles is more realistic for the observed delay propagation mechanism, and how robust airline scheduling methodologies can benefit from this probability-based delay model.

Suggested Citation

  • Weiwei Wu & Cheng-Lung Wu, 2018. "Enhanced delay propagation tree model with Bayesian Network for modelling flight delay propagation," Transportation Planning and Technology, Taylor & Francis Journals, vol. 41(3), pages 319-335, April.
    • Handle: RePEc:taf:transp:v:41:y:2018:i:3:p:319-335
    DOI: 10.1080/03081060.2018.1435453
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    Cited by:

    1. Jingyi Qu & Shixing Wu & Jinjie Zhang, 2023. "Flight Delay Propagation Prediction Based on Deep Learning," Mathematics, MDPI, vol. 11(3), pages 1-24, January.
    2. 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).

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