A NEW NONMONOTONE TRUST REGION ALGORITHM FOR SOLVING UNCONSTRAINED OPTIMIZATION PROBLEMS

被引：1
|
作者：
Liu, Jinghui [1 ]
Ma, Changfeng [1 ]
机构：
[1] Fujian Normal Univ, Sch Math & Comp Sci, Fuzhou 350007, Peoples R China
来源：
JOURNAL OF COMPUTATIONAL MATHEMATICS | 2014年 / 32卷 / 04期
基金：
中国国家自然科学基金;
关键词：
Unconstrained optimization problems; Nonmonotone trust region method; Global convergence; Superlinear convergence; LINE SEARCH TECHNIQUE; NEWTON METHOD; CONVERGENCE;
D O I：
10.4208/jcm.1401-m3975
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
Based on the nonmonotone line search technique proposed by Gu and Mo (Appl. Math. Comput. 55, (2008) pp. 2158-2172), a new nonmonotone trust region algorithm is proposed for solving unconstrained optimization problems in this paper. The new algorithm is developed by resetting the ratio rho(k) for evaluating the trial step d(k) whenever acceptable. The global and superlinear convergence of the algorithm are proved under suitable conditions. Numerical results show that the new algorithm is effective for solving unconstrained optimization problems.
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页码：476 / 490
页数：15
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