Interior-point gradient method for large-scale totally nonnegative least squares problems

被引：41

作者：

Merritt, M ^{[1
]}

Zhang, Y ^{[1
]}

机构：

[1] Rice Univ, Dept Computat & Appl Math, Houston, TX 77251 USA

来源：

JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS | 2005年 / 126卷 / 01期

基金：

美国国家科学基金会;

关键词：

totally nonnegative least-squares problems; interior-point gradient methods;

D O I：

10.1007/s10957-005-2668-z

中图分类号：

C93 [管理学]; O22 [运筹学];

学科分类号：

070105 ; 12 ; 1201 ; 1202 ; 120202 ;

摘要：

We study an interior-point gradient method for solving a class of so-called totally nonnegative least-squares problems. At each iteration, the method decreases the residual norm along a diagonally-scaled negative gradient direction with a special scaling. We establish the global convergence of the method and present some numerical examples to compare the proposed method with a few similar methods including the affine scaling method.

引用

页码：191 / 202

页数：12