A Modified Conjugacy Condition and Related Nonlinear Conjugate Gradient Method | Zendy

Shengwei Yao | Zendy; Xiwen Lu | Zendy; Bin Qin | Zendy

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A Modified Conjugacy Condition and Related Nonlinear Conjugate Gradient Method

Author(s) -

Shengwei Yao,

Xiwen Lu,

Bin Qin

Publication year - 2014

Publication title -

mathematical problems in engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.262

H-Index - 62

eISSN - 1026-7077

pISSN - 1024-123X

DOI - 10.1155/2014/710376

Subject(s) - nonlinear conjugate gradient method , conjugate gradient method , conjugacy class , mathematics , conjugate residual method , nonlinear system , derivation of the conjugate gradient method , gradient method , scale (ratio) , line search , conjugate , line (geometry) , mathematical optimization , mathematical analysis , computer science , gradient descent , pure mathematics , geometry , artificial intelligence , physics , quantum mechanics , artificial neural network , radius , computer security

The conjugate gradient (CG) method has played a special role in solving large-scale nonlinear optimization problems due to the simplicity of their very low memory requirements. In this paper, we propose a new conjugacy condition which is similar to Dai-Liao (2001). Based on this condition, the related nonlinear conjugate gradient method is given. With some mild conditions, the given method is globally convergent under the strong Wolfe-Powell line search for general functions. The numerical experiments show that the proposed method is very robust and efficient

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