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Smoothing Newton Method for Absolute Value Equations Based on Aggregate Function

机译:基于集合函数的光滑绝对值方程牛顿法

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We investigate the NP-hard absolute value equation (AVE) Ax-|x| = b, where A is an arbitrary square matrix whose all singular values of A exceed one. The significance of the absolute value equations arises from the fact that linear programs, quadratic programs, bimatrix games and other problems can all be reduced to the linear complementarity problem that in turn is equivalent to the absolute value equations. In this paper, we present a smoothing method for the AVE. First, we replace the absolute value function by a smooth one, called aggregate function. With this smoothing technique, we formulate the non-smooth AVE as a smooth nonlinear equations, furthermore, an unconstrained differentiable optimization problem. Then we adopt quasi-Newton method to solve this problem. Numerical results indicate that the method is feasible and effective to absolute value equations.
机译:我们研究NP硬绝对值方程(AVE)Ax- | x | = b,其中A是一个任意方阵,其A的所有奇异值均超过1。绝对值方程的重要性来自以下事实:线性程序,二次程序,双矩阵博弈和其他问题都可以简化为线性互补问题,而线性互补问题又等同于绝对值方程。在本文中,我们提出了AVE的平滑方法。首先,我们用一个平滑的绝对值函数代替了一个合计函数。利用这种平滑技术,我们将非平滑AVE公式化为平滑非线性方程,此外,还提出了无约束可微优化问题。然后我们采用准牛顿法来解决这个问题。数值结果表明,该方法对绝对值方程是可行且有效的。

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