Global convergence analysis of a new nonlinear conjugate gradient coefficient with strong wolfe line search
Nonlinear conjugate gradient (CG) methods are the most important method for solving largescale unconstrained optimisation problems. Many studies and modifications have been conducted recently to improve this method. In this paper, a new class of conjugate gradient coefficients β k with a new para...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Penerbit Universiti Kebangsaan Malaysia
2014
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| Online Access: | http://journalarticle.ukm.my/8296/ http://journalarticle.ukm.my/8296/ http://journalarticle.ukm.my/8296/1/jqma-10-1-paper7.pdf |
| Summary: | Nonlinear conjugate gradient (CG) methods are the most important method for solving largescale
unconstrained optimisation problems. Many studies and modifications have been conducted
recently to improve this method. In this paper, a new class of conjugate gradient coefficients
β k with a new parameter m = gk gk−1 that possesses global convergence properties is
presented. The global convergence and sufficient descent property is established using inexact
line searches to determine that α k is the step size of CG methods. Numerical result shows that
the new formula is superior and more efficient when compared to other CG coefficients. |
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