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Abstract
Except in adverse weather conditions, congestion at large airport hubs appears to be predictable.
This paper attempts to translate this predictability into a distribution of taxi-out times, a key
component of airport congestion. When scheduled flights are chosen to define the dataset, taxi-out
times follow a uniform distribution. This is not only the simplest distribution that inferences can be
based on, but also a distribution that can be estimated by simple linear regression leading to very
accurate forecasts. But above all, it is an invertible distribution function that can help solve a large
class of stochastic optimization problems.