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Korean Mathematical Society JKMS

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J. Korean Math. Soc. 2010; 47(1): 63-70

Printed January 1, 2010

https://doi.org/10.4134/JKMS.2010.47.1.63

Copyright © The Korean Mathematical Society.

A class of nonmonotone spectral memory gradient method

Zhensheng Yu, Jinsong Zang, and Jingzhao Liu

University of Shanghai for Science and Technology, University of Shanghai for Science and Technology, and Editorial Department of Journal of Qufu Normal University

Abstract

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In this paper, we develop a nonmonotone spectral memory gradient method for unconstrained optimization, where the spectral stepsize and a class of memory gradient direction are combined efficiently. The global convergence is obtained by using a nonmonotone line search strategy and the numerical tests are also given to show the efficiency of the proposed algorithm.

Keywords: unconstrained optimization, spectral memory gradient method, nonmonotone technique, global convergence

MSC numbers: 90C30, 65K05

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