A NEW NONMONOTONE TRUST REGION ALGORITHM FOR SOLVING UNCONSTRAINED OPTIMIZATION PROBLEMS

作     者：Jinghui Liu Changfeng Ma 

作者机构：School of Mathematics and Computer Science Fujian Normal University Fuzhou 350007 China 

出 版 物：《Journal of Computational Mathematics》 (计算数学（英文）)

年 卷 期：2014年第32卷第4期

页      面：476-490页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 07[理学] 070105[理学-运筹学与控制论] 0701[理学-数学] 

基　　金：国家自然科学基金 Fujian Natural Science Foundation R&D of Key Instruments and Technologies for Deep Resources Prospecting (the National R&D Projects for Key Scientific Instruments) 

主　　题：Unconstrained optimization problems Nonmonotone trust region method Global convergence Superlinear convergence. 

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 ρk for evaluating the trial step dk 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.