Semidefinite relaxation and nonconvex quadratic optimization

Abstract

In this paper we study the quality of semidefinite relaxation for a global quadratic optimization problem with diagonal quadratic consraints. We prove that such relaxation approximates the exact solution of the problem with relative accuracy μ = (π/2) – 1. We consider some applications of this result