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Predictive modeling of inbound demand at major European airports with Poisson and Pre-Scheduled Random Arrivals

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  • Lancia, Carlo
  • Lulli, Guglielmo

Abstract

This paper presents an exhaustive study of the arrivals process at eight major European airports. Using inbound traffic data, we define, compare, and contrast a data-driven in-homogeneous Poisson and Pre-Scheduled Random Arrivals (PSRA) point process with respect to their ability to predict future demand. As part of this analysis, we show the weaknesses and difficulties of using a non-homogeneous Poisson process to model the arrivals stream. On the other hand, our novel and simple data-driven (PSRA) model captures and predicts the main properties of the typical arrivals stream with good accuracy. These results have important implication for the modeling and simulation-based analyses of inbound traffic and can improve the use of available capacity, thus reducing air traffic delays. In a nutshell, the results lead to the conclusion that, in the European context, the (PSRA) model provides more accurate predictions.

Suggested Citation

  • Lancia, Carlo & Lulli, Guglielmo, 2020. "Predictive modeling of inbound demand at major European airports with Poisson and Pre-Scheduled Random Arrivals," European Journal of Operational Research, Elsevier, vol. 280(1), pages 179-190.
    • Handle: RePEc:eee:ejores:v:280:y:2020:i:1:p:179-190
    DOI: 10.1016/j.ejor.2019.06.056
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    Cited by:

    1. 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.

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