Nikolas Pyrgiotis

Massachusetts Institute of Technology

March 28, 2011, 14:15, Room GC B3 424 (click here for the map)

A Stochastic and Dynamic Model of Delay Propagation Within an Airport Network for Policy Analysis

<p>As more airports in the United States and in Europe become more congested, it also becomes increasingly likely that delays at one or more airports will spread to other parts of the network. We describe an analytical queuing and network decomposition model developed to study this complex phenomenon. The Airport Network Delays (AND) model computes the delays due to local congestion at individual airports and, more important, captures the "ripple effect" that leads to the propagation of these delays. The model operates by iterating between its two main components: a queuing engine (QE) that computes delays at individual airports and a delay propagation algorithm (DPA) that updates flight schedules and demand rates at all the airports in the model in response to the local delays computed by the QE. The QE is a stochastic and dynamic queuing model that treats each airport in the network as a M(t)/Ek(t)/1 queuing system. AND also includes an algorithm to model Ground Delay Programs.</p><p> The AND model is very fast computationally, thus making possible the exploration at a macroscopic level of the impacts of a large number of scenarios and policy alternatives on system-wide delays. AND has been implemented for two networks, one consisting of the 34 busiest airports in the continental United States and the other of the 19 busiest in Europe. It provides insights into the complex interactions through which delays propagate through the network and the often-counterintuitive consequences of these interactions. We are currently using AND to investigate a number of policy issues, such as the effect of implementing slot constrains at New York airports.</p>