Parametric Pivoting Algorithm for Parametric Quadratic Programming Problem

2009 Second Pacific-Asia Conference on Web Mining and Web-based Application Pub Date : 2009-06-06 DOI:10.1109/WMWA.2009.8

Yanwu Liu, Zhongzhen Zhang

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引用次数: 1

Abstract

There are many applications related to parametric quadratic programming. The parametric quadratic programming problem causes much more computation than the common quadratic programming problem. We employ the parametric pivoting algorithm to improve the computing efficiency of the parametric quadratic programming problem. The algorithm can decrease calculation to obtain solution of quadratic programming problem by solving a small linear inequality system which is the linear part of the Karush-Kuhn-Tucker (KKT) conditions for the quadratic programming problem and is equivalent to the KKT conditions while maintaining complementarity conditions of the KKT conditions to hold. The key of the algorithm is the deduction of the parametric formula which can obtain the optimal solution of the problem under new value of the parameter more efficiently by making full use of the information of the obtained optimal solution to the problem under former value of the parameter. The parametric formula further decreases the computation of the optimal solutions under different value of parameter.

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参数二次规划问题的参数旋转算法

有许多与参数二次规划有关的应用。参数二次规划问题比一般的二次规划问题计算量大得多。为了提高参数二次规划问题的计算效率，我们采用了参数旋转算法。该算法通过求解一个小的线性不等式系统来减少求解二次规划问题的计算量，该系统是二次规划问题的Karush-Kuhn-Tucker (KKT)条件的线性部分，在保持KKT条件的互补条件成立的同时等价于KKT条件。该算法的关键是参数公式的推导，通过充分利用得到的原参数值下问题最优解的信息，能更有效地求得新参数值下问题的最优解。参数公式进一步减少了不同参数值下最优解的计算量。

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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来源期刊

2009 Second Pacific-Asia Conference on Web Mining and Web-based Application

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