A NONMONOTONIC TRUST REGION TECHNIQUE FOR NONLINEAR CONSTRAINED OPTIMIZATION

被引：0
|
作者：
ZHU, DT [1 ]
机构：
[1] SHANGHAI NORMAL UNIV,SHANGHAI,PEOPLES R CHINA
来源：
JOURNAL OF COMPUTATIONAL MATHEMATICS | 1995年 / 13卷 / 01期
关键词：
D O I：
暂无
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
In this paper, a nonmonotonic trust region method for optimization problems with equality constraints is proposed by introducing a nonsmooth merit function and adopting a correction step. It is proved that all accumulation points of the iterates generated by the proposed algorithm are Kuhn-Tucker points and that the algorithm is q-superlinearly convergent.
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页码：20 / 31
页数：12
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