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P2: Improving Performance of the Interior Point Method by Preconditioning

Author: Kenneth Ryals , Advisor: Christopher C. Wright (JHU/APL)


Problem Statement Presentation

Project Proposal

Abstract

The Office of the Secretary of Defense/Acquisition and Technology (OSD/A&T), has a need for an optimization tool to use in their Distributed Command and Control System for nuclear assets. Several factors combine to imply that an Interior Point Method (IPM) for optimization would be applicable as it can easily address conic problems and it maintains iterate feasibility once a feasible point has been attained. The research proposed herein is intended to address the stability of the Interior Point Method in situations where the problem is ill conditioned. The normal equations for the IPM will be preconditioned using an inverse obtained from the constraint matrix (specifically the inverse of A.A') to reduce the condition number for ill-conditioned problems. The proposed enhancement will be tested on several benchmark datasets in the MPLIB and then shown to work on a representative for the OSD/A&T dataset.

MidYear Progress Report and Presentation

Final Presentation , Final Report