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

中文翻译：

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全局二次优化的充分条件

本文致力于n维实空间中二次优化问题的全局最优条件。更确切地说，我们关注具有线性约束的非凸二次优化问题。我们为受线性等式和不等式约束的此类问题提供了一些全局最优的充分条件。我们证明当该问题的Karush-Kuhn-Tucker三元组的集合是凸的时，则局部极小值是全局的