Interior point methods for solving Pareto eigenvalue complementarity problems

S. Adly, M. Haddou, Manh Hung Le
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引用次数: 3

Abstract

In this paper, we propose to solve Pareto eigenvalue complementarity problems by using interior-point methods. Precisely, we focus the study on an adaptation of the Mehrotra Predictor Corrector Method (MPCM) and a Non-Parametric Interior Point Method (NPIPM). We compare these two methods with two alternative methods, namely the Lattice Projection Method (LPM) and the Soft Max Method (SM). On a set of data generated from the Matrix Market, the performance profiles highlight the efficiency of MPCM and NPIPM for solving eigenvalue complementarity problems. We also consider an application to a concrete and large size situation corresponding to a geomechanical fracture problem. Finally, we discuss the extension of MPCM and NPIPM methods to solve quadratic pencil eigenvalue problems under conic constraints.
求解Pareto特征值互补问题的内点法
本文提出用内点法求解Pareto特征值互补问题。准确地说,我们重点研究了Mehrotra预测校正法(MPCM)和非参数内点法(NPIPM)的自适应。我们将这两种方法与两种替代方法,即点阵投影法(LPM)和软最大法(SM)进行了比较。在矩阵市场生成的一组数据上,性能概况突出了MPCM和NPIPM在解决特征值互补问题方面的效率。我们还考虑将其应用于与地质力学断裂问题相对应的混凝土和大尺寸情况。最后讨论了MPCM和NPIPM方法在二次约束下的二次铅笔特征值问题的推广。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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