Volume 15, Issue 1 (4-2018)                   jor 2018, 15(1): 19-28 | Back to browse issues page

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Babaei S, Arazm M. An extension of a three-term conjugate gradient method based on the objective function values with guaranteeing global convergence without convexity assumption . jor 2018; 15 (1) :19-28
URL: http://jamlu.liau.ac.ir/article-1-1329-en.html
An extension of a three-term conjugate gradient method based on the objective function values with guaranteeing global convergence without convexity assumption
S. Babaei * , M.R. Arazm
Associate Professor, Department of Mathematics, Faculty of Mathematics, Statistics and Computer Science, Semnan University, Semnan
Abstract:   (3563 Views)

With respect to importance of the conjugate gradient methods for large-scale optimization, in this study a descent three-term conjugate gradient method is proposed based on an extended modified secant condition. In the proposed method, objective function values are used in addition to the gradient information. Also, it is established that the method is globally convergent without convexity assumption on the objective function. Numerical experiments show reasonable computational efficiency of the suggested method.
 

Keywords: unconstrained optimization, large-scale optimization, conjugates gradient method, secant condition, global convergence
Full-Text [PDF 219 kb]   (2406 Downloads)    
Type of Study: Research | Subject: Special
Received: 2016/09/17 | Accepted: 2017/03/4 | Published: 2018/03/11
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