Global and local convergence of a new affine scaling trust region algorithm for linearly constrained optimization

被引：3

作者：

Gu, Chao ^{[1
]}

Zhu, De Tong ^{[2
]}

机构：

[1] Shanghai LiXin Univ Commerce, Sch Math & Informat, Shanghai 201620, Peoples R China

[2] Shanghai Normal Univ, Dept Math, Shanghai 200234, Peoples R China

来源：

ACTA MATHEMATICA SINICA-ENGLISH SERIES | 2016年 / 32卷 / 10期

基金：

中国国家自然科学基金;

关键词：

Linearly constrained optimization; affine scaling; trust region; dwindling filter; convergence; INTERIOR-POINT ALGORITHMS; FILTER SQP ALGORITHM; KERNEL FUNCTION; SEARCH METHOD;

D O I：

10.1007/s10114-016-4513-8

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

Chen and Zhang [Sci. China, Ser. A, 45, 1390-1397 (2002)] introduced an affine scaling trust region algorithm for linearly constrained optimization and analyzed its global convergence. In this paper, we derive a new affine scaling trust region algorithm with dwindling filter for linearly constrained optimization. Different from Chen and Zhang's work, the trial points generated by the new algorithm are accepted if they improve the objective function or improve the first order necessary optimality conditions. Under mild conditions, we discuss both the global and local convergence of the new algorithm. Preliminary numerical results are reported.

引用

页码：1203 / 1213

页数：11

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