Models and Algorithms for Transient Queueing Congestion at a Hub Airport

This paper studies the relationship between the hub-and-spoke design in air transportation and the phenomenon of landing congestion in a transient environment. We model the weather, the principal source of uncertainty, as a Markov or semi-Markov process, and we treat arrivals as time-varying but deterministic. We develop a recursive algorithm for predicting transient queueing delays. To test our model, we conduct a case study using traffic and capacity data for Dallas-Fort Worth International Airport. Our results show that the model's estimates are reasonable, though substantial data difficulties make thorough validation difficult. We explore in depth two policy questions: schedule interference between the two principal carriers, and the likely effects of demand smoothing policies on queueing delays.