A sufficient conditions for global quadratic optimization
This paper is devoted to global optimality conditions for quadratic optimization problems in a real space of dimension n. More precisely, we are concerned with nonconvex quadratic optimization problems with linear constraints. We present some sufficient conditions of global optimality for such problems subject to linear equality and inequality constraints. We prove that when the set of Karush-Kuhn-Tucker triplets of this problem is convex, then a local minimizer is global
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