CONVERGENCE PROPERTY AND MODIFICATIONS OF A MEMORY GRADIENT METHOD

Zhen-Jun Shi () and Jie Shen ()
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Zhen-Jun Shi: College of Operations Research & Management, Qufu Normal University, Rizhao, Shandong 276826, China;
Jie Shen: Department of Computer & Information Science, University of Michigan, Dearborn, MI 48128, USA

Asia-Pacific Journal of Operational Research (APJOR), 2005, vol. 22, issue 04, 463-477

Abstract: We study properties of a modified memory gradient method, including the global convergence and rate of convergence. Numerical results show that modified memory gradient methods are effective in solving large-scale minimization problems.

Keywords: Unconstrained optimization; memory gradient method; exact line search; convergence (search for similar items in EconPapers)
Date: 2005
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Persistent link: https://EconPapers.repec.org/RePEc:wsi:apjorx:v:22:y:2005:i:04:n:s0217595905000625

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DOI: 10.1142/S0217595905000625

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