A NEW TRUST-REGION ALGORITHM FOR FINITE MINIMAX PROBLEM

被引：4

作者：

Wang, Fusheng ^{[1
]}

Wang, Chuanlong ^{[1
]}

Wang, Li ^{[2
]}

机构：

[1] Taiyuan Normal Univ, Dept Math, Taiyuan 030012, Peoples R China

[2] Univ Calif San Diego, Dept Math, San Diego, CA 92103 USA

来源：

JOURNAL OF COMPUTATIONAL MATHEMATICS | 2012年 / 30卷 / 03期

基金：

中国国家自然科学基金;

关键词：

Trust-region methods; Minimax optimization; Nonmonotone strategy; Global convergence; Superlinear convergence; NONMONOTONE LINE SEARCH; SUPERLINEAR CONVERGENCE; SQP ALGORITHM;

D O I：

10.4208/jcm.1109-m3567

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In this paper, a new trust region algorithm for minimax optimization problems is proposed, which solves only one quadratic subproblem based on a new approximation model at each iteration. The approach is different with the traditional algorithms that usually require to solve two quadratic subproblems. Moreover, to avoid Maratos effect, the nonmonotone strategy is employed. The analysis shows that, under standard conditions, the algorithm has global and superlinear convergence. Preliminary numerical experiments are conducted to show the effiency of the new method.

引用

页码：262 / 278

页数：17

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