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Extended trust-region problems with one or two balls: exact copositive and Lagrangian relaxations

机译:具有一个或两个球的扩展信任区域问题:精确的共正松弛和拉格朗日松弛

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摘要

We establish a geometric condition guaranteeing exact copositive relaxation for the nonconvex quadratic optimization problem under two quadratic and several linear constraints, and present sufficient conditions for global optimality in terms of generalized Karush–Kuhn–Tucker multipliers. The copositive relaxation is tighter than the usual Lagrangian relaxation. We illustrate this by providing a whole class of quadratic optimization problems that enjoys exactness of copositive relaxation while the usual Lagrangian duality gap is infinite. Finally, we also provide verifiable conditions under which both the usual Lagrangian relaxation and the copositive relaxation are exact for an extended CDT (two-ball trust-region) problem. Importantly, the sufficient conditions can be verified by solving linear optimization problems.
机译:我们建立了一个几何条件,在两个二次和几个线性约束下,保证了非凸二次优化问题的精确正松弛,并为广义Karush-Kuhn-Tucker乘子的全局最优性提供了充分的条件。正松弛比通常的拉格朗日松弛更紧密。我们通过提供一类完整的二次优化问题来说明这一点,这些问题享有共正松弛的精确性,而通常的拉格朗日对偶间隙是无限的。最后,我们还提供了可验证的条件,在该条件下,通常的拉格朗日弛豫和共正弛豫均适用于扩展CDT(两球信任区域)问题。重要的是,可以通过解决线性优化问题来验证充分条件。

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