Combining Exact and Heuristic Approaches for Discrete Optimization
Abstract
In the last decade the computational power of discrete optimization methodology has increased remarkably to the point where problems that could not be solved with days of computation can now be solved in minutes by commercial solvers. This success has stimulated the need for methodology to solve even much larger problems and the desire to solve problems in real-time. We have conducted research that has yielded computationally effective algorithms to provide high-quality solutions to very large-scale planning problems and high-quality solutions in (nearly) real-time to operational problems. Traditionally, this goal has been pursued with heuristic approaches.
Document Details
- Document Type
- Technical Report
- Publication Date
- Feb 18, 2009
- Accession Number
- ADA495432
Entities
People
- George L. Nemhauser
- Martin W. Savelsbergh
Organizations
- Georgia Tech Research Corporation