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SUMMARY:A Stochastic and Dynamic Policy-Oriented Model of a Large Network 
 of Airports
DTSTART:20100125T150000
DTSTAMP:20260510T064847Z
UID:691d8bcb318690fffa86135a6f6a05d6e13e92d2761ef63d5a28ea02
CATEGORIES:Conferences - Seminars
DESCRIPTION:Prof. Amedeo Odoni\, Massachusetts Institute of Technology\nAs
  more airports in the United States and in Europe become congested\, it al
 so becomes increasingly likely that delays at one or more airports will sp
 read to other parts of the network. We describe an analytical model\, Airp
 ort Network Delays (AND)\, developed to study this complex phenomenon. It 
 computes delays due to local congestion at individual airports and\, more 
 important\, captures the "ripple effect" that leads to the propagation of 
 local delays throughout the network. The model operates by iterating betwe
 en a stochastic and dynamic queuing engine (QE) that computes delays at in
 dividual airports and a delay propagation algorithm that updates flight sc
 hedules at all the airports in the model in response to the local delays c
 omputed by the QE.\n\nThe AND model is fast computationally\, making possi
 ble the exploration of the impacts of a large number of scenarios and poli
 cies on system-wide delays. It has been fully implemented for the network 
 of the 34 busiest airports in the continental United States. An implementa
 tion for the network of the 34 busiest airports in Europe is in progress. 
 The model provides insights into the complex interactions through which de
 lays propagate through the network and the often-counterintuitive conseque
 nces of these interactions. (joint work with PhD student Nikolas Pyrgiotis
 )
LOCATION:GC B3 424
STATUS:CONFIRMED
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