Polynomial-time interior-point algorithm based on a local self-concordant finite barrier function

被引：0

作者：

金正静 ^{[1
,2
]}

白延琴 ^{[1
]}

机构：

[1] College of Sciences, Shanghai University

[2] College of Sciences, Zhejiang Forestry University

来源：

Advances in Manufacturing | 2009年 / 13卷 / 04期

基金：

中国国家自然科学基金;

关键词：

linear optimization; self-concordant function; finite barrier; interior-point methods; polynomial-time complexity;

D O I：

暂无

中图分类号：

O224 [最优化的数学理论];

学科分类号：

070105 ; 1201 ;

摘要：

The choice of self-concordant functions is the key to efficient algorithms for linear and quadratic convex optimiza-tions,which provide a method with polynomial-time iterations to solve linear and quadratic convex optimization problems.The parameters of a self-concordant barrier function can be used to compute the complexity bound of the proposed algorithm.In this paper,it is proved that the finite barrier function is a local self-concordant barrier function.By deriving the local values of parameters of this barrier function,the desired complexity bound of an interior-point algorithm based on this local self-concordant function for linear optimization problem is obtained.The bound matches the best known bound for smallupdate methods.

引用

页码：333 / 339

页数：7