Efficient primal-dual interior-point methods for non-symmetric cone programming
Abstract
The goal of this methodology-focused project is to develop new, efficient algorithms and computational tools for a large class of optimization problems called non-symmetric conic programming problems that are customizable and scalable for a wide range of applications. Unlike symmetric conic programming problems (e.g., linear and semidefinite programming), non-symmetric cone programming has minimal algorithmic support and virtually no reliable software available to the community, despite its wide range of applications. The primary goal of the project is to address this need. A major emphasis of the project is motivated by certified computations applied, for instance, in rigorous system and model verification for mission-critical systems, where numerical methods have recently become popular as highly-efficient building blocks. The research will provide a theoretical and algorithmic foundation to solve a wider class of non-symmetric conic optimization problems than currently possible using state-of-the-art algorithms and software, and to combine this foundation with a rigorous certification framework applicable to certified computing. Although the proposed project is focused on algorithmic development, every algorithm developed in the project will also be implemented and tested in large-scale applications from the PI’s ongoing collaborations.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Mar 06, 2024
- Source ID
- FA95502310370
Entities
People
- David Papp
Organizations
- Air Force Office of Scientific Research
- North Carolina State University
- United States Air Force