A globally convergent BFGS method with nonmonotone line search for non-convex minimization
type: Item
instance of: scholarly article
title: A globally convergent BFGS method with nonmonotone line search for non-convex minimization
zbMATH Open document ID: 1169.65058
author: Huijuan Sun
author: Yunhai Xiao
author: Zhiguo Wang
published in: Journal of Computational and Applied Mathematics
publication date: 2009-06-25T00:00:00Z
review text: A modified nonmonotone BFGS (Broyden-Fletcher-Goldfarb-Shanno) method is developed for solving unconstrained optimization problems. In the proposed method, the function value at each iteration allows for an occasional increase. The method can converge to a local optimal point without a convex assumption on the objective functions. The global convergence is established under certain conditions. Some numerical experimental results are presented to compare its performance with the monotone BFGS method.
Mathematics Subject Classification ID: 65K05
Mathematics Subject Classification ID: 90C30
zbMATH DE Number: 5570559
zbMATH Keywords: non-convex minimization
zbMATH Keywords: secant equation
zbMATH Keywords: BFGS method
zbMATH Keywords: nonmonotone line search
zbMATH Keywords: global convergence
zbMATH Keywords: numerical examples
zbMATH Keywords: Broyden-Fletcher-Goldfarb-Shanno method
zbMATH Keywords: unconstrained optimization
MaRDI profile type: Publication
full work available at URL: j.cam.2008.10.065
OpenAlex ID: W2136317623
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DOI: 10.1016/J.CAM.2008.10.065
description: scientific article; zbMATH DE number 5570559