New RLT Theory for Solving Continuous Nonlinear and Mixed-Discrete Optimization Problems
Abstract
Abstract This project is to develop new solution strategies and algorithmic frameworks for solving families of continuous nonlinear and mixed-discrete optimization problems. These problems are well-recognized as being extremely challenging mathematically, while at the same time having important applications in numerous areas such as engineering design, facility layout and location, logistics, mission planning, production planning and control, resource allocation, and transportation science. State-of-the-art solution procedures lag far behind societal needs, so research advances can have significant positive impact in various venues. The main research thrust is to develop a comprehensive new theory that extends the “reformulation-linearization-technique” (RLT) convex hull results for mixed-discrete polynomial programs to encompass continuous, nonconvex programs, and to use this newfound theory as the foundation for global optimization methods. A secondary thrust is to invoke existing RLT constructs to unify and extend recent theoretical contributions for the quadratic assignment and traveling salesman problems, and to implement the findings, where suitable, as the basis for improved solution algorithms.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jun 03, 2016
- Source ID
- N000141612168
Entities
People
- Warren Adams
Organizations
- Clemson University
- Office of Naval Research
- United States Navy