Abstract
In the field of robust flight optimization, disruption and delay propagation play a central role. Recently, huge amounts of data became available for analysis of these delays. For example, empirical distribution functions can be estimated and used as input for scheduling systems. But for a better understanding of the underlying mechanisms, distribution models with explicit dependencies and interpretable parameters are more desirable. In this paper we present new patterns in flight delay data and an initial model of the underlying physical processes.
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© 2014 Springer International Publishing Switzerland
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Ionescu, L., Gwiggner, C., Kliewer, N. (2014). Empirical and Mechanistic Models for Flight Delay Risk Distributions. In: Helber, S., et al. Operations Research Proceedings 2012. Operations Research Proceedings. Springer, Cham. https://doi.org/10.1007/978-3-319-00795-3_86
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DOI: https://doi.org/10.1007/978-3-319-00795-3_86
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Online ISBN: 978-3-319-00795-3
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