Treating Difficult Nonlinearities in Optimization: Sparse, Global and Integer Optimization
Abstract
For mixed-integer linear programming and local nonlinear programming, over the last 50+ years, good modeling practices have become well known, and many important mathematical and algorithmic principles are now absorbed by solvers. For other important categories of optimization problems, mathematical and algorithmic theory and practice are much less developed. We are addressing several key issues: optimizing sparsity, handling non-smooth and nonconvex functions in the context of global optimization, and integrality issues which become amplified by nonlinearities.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Mar 03, 2017
- Source ID
- N000141712296
Entities
People
- Jon Lee
Organizations
- Board of Regents of the University of Michigan
- Office of Naval Research
- United States Navy