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.

Language

  • English

Media Info

  • Pagination: 22 p.

Subject/Index Terms

Filing Info

  • Accession Number: 00730691
  • Record Type: Publication
  • Report/Paper Numbers: AFOSR-TR-96-0206
  • Files: NTL, TRIS
  • Created Date: Feb 3 1997 12:00AM