Building Reliable Air Travel Infrastructure Using 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. A recent report by the Joint Economic Committee of the U.S. Congress has estimated that the total cost to the U.S. economy due to flight delays was as much as $41 billion in 2007.
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 network based passenger-centric metrics could be used by the FAA to measure on-time performance and schedule robustness? Which are the bottleneck airports in the U.S. air travel infrastructure (i.e., airports that cause most delay propagation)? How would increasing airport capacity at these airports alleviate delay propagation? Which airlines have the least robust schedules? How could these schedules be made more robust?