A globally convergent BFGS method with nonmonotone line search for non-convex minimization

JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS

卷:230

Article

Xiao, Yunhai^1,2  Sun, Huijuan²  Wang, Zhiguo² 

[1] Nanjing Univ, Dept Math, Nanjing 210093, Peoples R China

[2] Henan Univ, Inst Appl Math, Coll Math & Informat Sci, Kaifeng 475004, Peoples R China

关键词: Non-convex minimization;    Secant equation;    BFGS method;    Nonmonotone line search;    Global convergence;   

DOI  :  10.1016/j.cam.2008.10.065

来源: Elsevier

【 摘 要 】

In this paper, we propose a modified BFGS (Broyden-Fletcher-Goldfarb-Shanno) method with nommonotone line search for unconstrained optimization. Under some mild conditions, we show that the method is globally convergent without a convexity assumption on the objective function. We also report some preliminary numerical results to show the efficiency of the proposed method. Crown Copyright (C) 2008 Published by Elsevier B.V. All rights reserved.

【 授权许可】

Free