Canonical Duality Theory and Algorithm for Solving NP-Hard Problems in Decision Science and Complex Systems
Abstract
The main goal of this project is to advance Canonical Duality theory and to develop a powerful deterministic method and polynomial algorithms for solving general Mixed Integer Nonlinear Programming (MINLP) problems in decision science, thereby achieving substantial cost reductions across a wide range of military and defense industries.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- May 02, 2017
- Source ID
- FA95501710151
Entities
People
- David Gao
Organizations
- Air Force Office of Scientific Research
- Federation University Australia
- United States Air Force