This $250,000 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program supports research by the University of California, San Diego (UCSD) on the development of "tight relaxation methods" for solving challenging optimization problems, such as polynomial optimization, generalized Nash equilibria, and matrix-constrained polynomial optimization. The project aims to create efficient computational methods for locating global optimal solutions to these types of non-linear, non-convex optimization problems, which have broad applications in science and engineering. Key research tasks include advancing Lagrange multiplier expressions, sum of squares, moment relaxations, and semidefinite programs to enable solving these hard optimization problems. The award period runs from July 2025 through June 2028.
Mod # | Description | Reason For Modification | Federal Obligation (Click to sort descending) | Date (Click to sort ascending) |
|---|---|---|---|---|
| Not listed | $250.0k | 7/10/25 |