TITLE:
An Effective Algorithm for Quadratic Optimization with Non-Convex Inhomogeneous Quadratic Constraints
AUTHORS:
Kaiyao Lou
KEYWORDS:
Nonconvex Inhomogeneous Quadratic Constrained Quadratic Optimization, Semidefinite Programming Relaxation, Np-Hard
JOURNAL NAME:
Advances in Pure Mathematics,
Vol.7 No.4,
April
30,
2017
ABSTRACT: This paper considers the NP (Non-deterministic Polynomial)-hard problem of finding a minimum value of a quadratic program (QP), subject to m non-convex inhomogeneous quadratic constraints. One effective algorithm is proposed to get a feasible solution based on the optimal solution of its semidefinite programming (SDP) relaxation problem.