A Proximal Bundle Method Based on Approximate Subgradients

被引：0

作者：

Michael Hintermüller

机构：

[1] Institute of Mathematics,

[2] Karl-Franzens-University of Graz,undefined

来源：

Computational Optimization and Applications | 2001年 / 20卷

关键词：

approximate subgradient; convex programming; nonsmooth optimization; proximal bundle method;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

In this paper a proximal bundle method is introduced that is capable to deal with approximate subgradients. No further knowledge of the approximation quality (like explicit knowledge or controllability of error bounds) is required for proving convergence. It is shown that every accumulation point of the sequence of iterates generated by the proposed algorithm is a well-defined approximate solution of the exact minimization problem. In the case of exact subgradients the algorithm behaves like well-established proximal bundle methods. Numerical tests emphasize the theoretical findings.

引用

页码：245 / 266

页数：21