ARTIFICIAL INTELLIGENCE METHODOLOGIES IN AIR TRANSPORTATION NETWORK ROUTING AND SCHEDULING
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; 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; time dependent integer programming, using time sweeps; and other appropriate tools and techniques.
- Record URL:
Washington University, St LouisDepartment of Systems Science and Mathematics
St Louis, MO United States 63130
- Rodin, E
- Publication Date: 1996-1-31
- Pagination: 22 p.
- TRT Terms: Air transportation; Artificial intelligence; Decision making; Expert systems; Mathematical methods; Networks; Routing; Scheduling
- Subject Areas: Aviation; Operations and Traffic Management;
- Accession Number: 00730691
- Record Type: Publication
- Report/Paper Numbers: AFOSR-TR-96-0206
- Files: NTL, TRIS
- Created Date: Feb 3 1997 12:00AM