Building reliable air-travel infrastructure using empirical data and stochastic models of airline networks

Flight delays have been a growing issue and they have reached an all-time high in recent years, with the
airlines’ on-time performance at its worst level in 2007 since 1995. The goal of this paper is to build stochastic
models of airline networks and utilize publicly available data to answer the following policy questions: Which
are the bottleneck airports in the US air-travel infrastructure? How would increasing airport capacity at
these airports alleviate delay propagation? What are the appropriate metrics for measuring the robustness
of airline schedules? How could these schedules be made more robust? Which flight in an aircraft rotation
is a bottleneck flight? The contribution of this paper is two-fold. First, we develop stochastic models, using
empirical data, to analyze the propagation of delays through air-transportation networks. Second, our analysis
enables us to make policy recommendations regarding managing bottleneck resources in the air-travel
infrastructure