Systems of quadratic equations: Efficient solution algorithms and conditions for solvability

Krishnamurthy Dvijotham
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引用次数: 1

Abstract

We study multivariate systems of quadratic equations of the form F (x) = s where F : ℝn → ℝn and Fi a quadratic function of x for i = 1, ..., n. These types of equations arise across a variety of applications including sensor network localization, power systems and matrix factorization. In general, solving systems of quadratic equations is a challenging task, and in its most general form is NP-hard. In this paper, we approach this problem from a different perspective: We characterize domains over which the problem can be solved efficiently. For any such domain, we develop an efficient algorithm that terminates with: a) a solution in the domain, or b) a certificate of non-existence of the solution in the domain. Further, we derive conditions on s that guarantee the existence of a solution in the domain. We show how this result can be used to construct convex inner approximations to the feasible set of a Quadratically Constrained Quadratic Program (QCQP). Finally, we illustrate the results on simple examples from these application domains.
二次方程系统:有效解算法和可解性条件
我们研究了形式为F (x) = s的多元二次方程系统,其中F:∈n→∈n, Fi是x的二次函数,当i = 1,…这些类型的方程出现在各种应用中,包括传感器网络定位,电力系统和矩阵分解。一般来说,求解二次方程系统是一项具有挑战性的任务,其最一般的形式是np困难。在本文中,我们从不同的角度来处理这个问题:我们描述了问题可以有效解决的领域。对于任何这样的域,我们开发了一个有效的算法,该算法以:a)域中的解,或b)域中不存在解的证书结束。进一步,我们导出了s上保证解在定义域内存在的条件。我们展示了如何利用这一结果构造二次约束二次规划可行集的凸内逼近。最后,我们用来自这些应用领域的简单示例来说明结果。
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