A Modified Non-Monotone BFGS Method for Non-Convex Unconstrained Optimization

Liying Liu (), Shengwei Yao () and Zengxin Wei ()
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Liying Liu: College of Mathematics Science, Liaocheng University, 1 Hunan Avenue, Liaocheng, Shandong 252059, P. R. China
Shengwei Yao: School of Science, East China University of Science and Technology, Shanghai 200237, P. R. China;
Zengxin Wei: College of Mathematics and Information Science, Guangxi University, 10 Daxue Avenue, Nanning, Guangxi 530004, P. R. China

Asia-Pacific Journal of Operational Research (APJOR), 2014, vol. 31, issue 05, 1-15

Abstract: In this paper, a modified non-monotone BFGS (MNBFGS) method for non-convex unconstrained optimization is proposed. Under some mild conditions, the global convergence of the given method is established, when the objective function is non-convex. Preliminary numerical comparisons, which show the proposed method is competitive, are also reported.

Keywords: Non-convex optimization; BFGS method; non-monotone line search; global convergence (search for similar items in EconPapers)
Date: 2014
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DOI: 10.1142/S021759591450033X

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