Optimal algorithms for large sparse quadratic programming problems with uniformly bounded spectrum

被引：0

作者：

Dostál, Z ^{[1
]}

机构：

[1] Tech Univ Ostrava, VSB, CZ-70833 Ostrava, Czech Republic

来源：

LARGE-SCALE NONLINEAR OPTIMIZATION | 2006年 / 83卷

关键词：

quadratic programming; box and equality constraints; augmented Lagrangians; adaptive precision control;

D O I：

暂无

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

Recently proposed algorithms for the solution of large quadratic programming problems are reviewed. An important feature of these algorithms is their capability to find an approximate solution of the convex equality and/or bound constrained quadratic programming problems with the uniformly bounded spectrum of the Hessian matrix at O(1) iterations. The theoretical results are presented and illustrated by numerical experiments.

引用

页码：83 / 93

页数：11

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