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DC Programming Approach for Asymmetric Eigenvalue Complementarity Problem

机译:不对称特征值互补问题的直流规划方法

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摘要

We propose a DC (Difference of Convex fonctions) programming approach for solving asymmetric eigenvalue complementarity problem (EiCP). This problem is equivalent to a Nonlinear Program (NLP) that minimizing a nonconvex polynomial merit function on a convex set defined by linear constraints. EiCP has a solution if and only if NLP has zero global optimal value. We will reformulate the NLP as a DC Program (DCP) and then solve the later one by an efficient DC Algorithm (DCA). Some preliminary numerical results are also reported.
机译:我们提出了一种DC(凸函数的差分)编程方法来解决非对称特征值互补问题(EiCP)。此问题等效于非线性程序(NLP),它将非线性约束定义的凸集上的非凸多项式优函数最小化。当且仅当NLP的全局最优值为零时,EiCP才有解决方案。我们将把NLP重新格式化为DC程序(DCP),然后通过高效的DC算法(DCA)解决后者。还报告了一些初步的数值结果。

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