ON THE GLOBAL CONVERGENCE OF TRUST REGION ALGORITHMS USING INEXACT GRADIENT INFORMATION

被引：68

作者：

CARTER, RG ^{[1
]}

机构：

[1] RICE UNIV,DEPT MATH SCI,HOUSTON,TX 77251

来源：

SIAM JOURNAL ON NUMERICAL ANALYSIS | 1991年 / 28卷 / 01期

关键词：

UNCONSTRAINED OPTIMIZATION; TRUST REGION METHODS; INEXACT GRADIENTS; GLOBAL CONVERGENCE;

D O I：

10.1137/0728014

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

Trust region algorithms are an important class of methods that can be used to solve unconstrained optimization problems. Strong global convergence results are demonstrated for a class of methods where the gradient values are approximated rather than computed exactly, provided they obey a simple relative error condition. No requirement is made that gradients be recomputed to successively greater accuracy after unsuccessful iterations.

引用

页码：251 / 265

页数：15

共 15 条

[1]

[Anonymous], 1970, NONLINEAR PROGRAMMIN, DOI DOI 10.1016/B978-0-12-597050-1.50006-3

[2]

CARTER R, 1989, UNPUB SIAM J SCI STA

[3]

CARTER RG, 1987, TR8706 RIC U DEP MAT

[4] 2 NEW UNCONSTRAINED OPTIMIZATION ALGORITHMS WHICH USE FUNCTION AND GRADIENT VALUES [J].