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

By James DeArmon , Christine Taylor , Tudor Masek , Craig Wanke

A network queuing model of the NAS supports research into a strategic air traffic flow management capability. To reduce the network size for the model, we investigate route clustering, i.e., grouping routes to reduce the number of paths between airports.

Download Resources


PDF Accessibility

One or more of the PDF files on this page fall under E202.2 Legacy Exceptions and may not be completely accessible. You may request an accessible version of a PDF using the form on the Contact Us page.

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.​