Artificial Intelligence Methodologies in Air Transportation Network Routing and Scheduling.
Abstract
As stated in previous years' reports, the purpose of this research project was to develop a generic model and methodology for analyzing and optimizing large scale air transportation networks, including both their routing and their scheduling. Our methodology to achieve this aim consists in part by studying several specific examples of current problems of this type, arising in the operations of the Air Mobility Command (AMC) at Scott AFB; and in part by developing further the various paradigms that we had employed successfully in the past in similar contexts. These include the utilization of the classical mathematical methodologies of Linear and Integer Programming, in conjunction with Neural Networks clustering algorithms; rule-based Expert Systems; various decision methodologies, such as the Analytic Hierarchy Process; Voronoi diagrams and Delaunay triangulations (for initialization purposes); time dependent integer programming, using Time Sweeps; and other appropriate tools and techniques. We also found it absolutely necessary and very useful to continue to collaborate even more extensively than in the past with military scientists from Scott AFB. Finally, we should note that all of the objectives of the original proposal have been met, and the results obtained are currently being extended. In addition, several new initiatives, with various elements of the USAF at Scott AFB (HQ/AMC, USTRANSCOM, Command Surgeon) were undertaken and are also currently being studied.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 31, 1996
- Accession Number
- ADA308269
Entities
People
- Ervin Rodin
Organizations
- University of Washington