The National Science Foundation (NSF) awarded a $303,823 Project Grant under the Engineering program (CFDA 47.041) to the Regents of the University of Minnesota, with a performance period from August 1, 2024 to July 31, 2025. This grant will contribute to the advancement of national health, prosperity, and welfare by developing a computational framework to efficiently solve a large class of inverse optimization models. The methodology will be applied to system identification problems in cancer radiotherapy to help validate current treatment protocols. The project will pursue two approaches to solve these nonconvex, bilinear inverse optimization models: (1) conversion into equivalent convex problems via variable transformation, and (2) a suite of tailored approximation algorithms. The researched methods will be evaluated computationally against classic branch-and-bound algorithms using publicly available data sets, as well as through an in-depth case study in cancer radiotherapy. The principal investigator will also mentor doctoral students on this research topic and incorporate the results into a graduate-level course and two new books, as well as workshops and seminars on optimization applications for underrepresented STEM students.
Mod # | Description | Reason For Modification | Federal Obligation (Click to sort descending) | Date (Click to sort ascending) |
|---|---|---|---|---|
| Not listed | $303.8k | 9/16/24 |