1 Air Route Clustering for a Queuing Network Model of the National Airspace System

A network queuing model of the National Airspace System has been developed to support research into a strategic air traffic flow management capability. One of the challenges in the execution of the model is the size of the network – the computing resources required when modeling the entire United States are immense. As a way to reduce the network size, we investigate route clustering, i.e., grouping similar routes to reduce the number of paths between two airports. Clustering routes comes at a cost: as the number of clusters falls, the with-in cluster variability rises, and the solution quality is diminished. A trade-off curve for solution quality vs. cluster variability is developed for a sample problem involving seven major airports. I. Introduction/Background A prototype capability for strategic air traffic flow management is undergoing research and development. The capability, called Flow Contingency Management (FCM), will supply automated decision support for what currently is a mostly manual process.1 It is recognized that strategic decisions made with a 2- to 24-hour time horizon will likely improve air traffic flows in the National Airspace System (NAS) by averting large-scale traffic congestion du