Extending the Reformulation Linearization Technique to Continuous, Nonconvex Problems
Abstract
This effort is to develop a new framework for solving continuous, nonconvex optimization problems. These type problems commonly arise in such areas as engineering design, mission planning, and resource allocation. The project will develop an encompassing Reformulation Linearization Technique (RLT) theory that accommodates nonlinear expressions of continuous variables. The RLT is a general procedure for recasting discrete optimization problems into higher variables spaces for the purpose of obtaining tight polyhedral outer approximations of the convex hull of feasible solutions.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jan 14, 2022
- Source ID
- FA95501910339
Entities
People
- Boshi Yang
Organizations
- Air Force Office of Scientific Research
- Clemson University
- United States Air Force