ALGORITHMIC AND INFORMATION COMPLEXITY OF MIXED-INTEGER CONVEX OPTIMIZATION
Abstract
The project will develop new theoretical foundations for mixed-integer convex optimization and propose tools to enhance existing methods based on these insights. If successful, these insights will unify classical work in continuous convex optimization with insights from discrete optimization and geometry, providing the tightest bounds on the complexity of this fundamental problem. In addition to contributing to a long and rich line of work on mixed-integer optimization, the research will develop new techniques to further improve state-of-the-art software for solving mixed-integer optimization models. Advances are expected to have impact in diverse application areas such as computational game theory applied to national security and defense, chemical engineering, astronomical data analysis, and smart cities initiatives, amongst many others.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Feb 06, 2025
- Source ID
- FA95502510038
Entities
People
- Amitabh Basu
Organizations
- Air Force Office of Scientific Research
- Johns Hopkins University
- United States Air Force