Home > Research > Publications & Outputs > Predictive modeling of inbound demand at major ...

Electronic data

  • LL_EJOR

    Rights statement: This is the author’s version of a work that was accepted for publication in European Journal of Operational Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in European Journal of Operational Research, 280, 1, 2020 DOI: 10.1016/j.ejor.2019.06.056

    Accepted author manuscript, 8.12 MB, PDF document

    Embargo ends: 17/07/21

    Available under license: CC BY-NC-ND: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License

  • LL_Appendix

    Other version, 3.6 MB, PDF document

    Available under license: CC BY-NC-ND: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License

Links

Text available via DOI:

View graph of relations

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

Research output: Contribution to journalJournal article

Published
<mark>Journal publication date</mark>1/01/2020
<mark>Journal</mark>European Journal of Operational Research
Issue number1
Volume280
Number of pages12
Pages (from-to)179-190
Publication statusPublished
Original languageEnglish

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.

Bibliographic note

This is the author’s version of a work that was accepted for publication in European Journal of Operational Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in European Journal of Operational Research, 280, 1, 2020 DOI: 10.1016/j.ejor.2019.06.056