A new nonlinear conjugate gradient method
Conjugate gradient (CG) methods are essential for solving large-scale unconstrained optimization problems. Many of studies and modifications have been practiced to improve this method. In this paper, a new class of conjugate gradient coefficients (βk) with a new parameter m = ‖gk‖‖dk−1‖ that possess...
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Format: | Tagungsbericht |
Sprache: | eng |
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Zusammenfassung: | Conjugate gradient (CG) methods are essential for solving large-scale unconstrained optimization problems. Many of studies and modifications have been practiced to improve this method. In this paper, a new class of conjugate gradient coefficients (βk) with a new parameter m = ‖gk‖‖dk−1‖ that possess global convergence properties is presented. The global convergence and sufficient decent property result is established using inexact line searches to determine the step size of CG, denoted as ∝k. Numerical result shows that the new formula is superior and more efficient when compared to other CG coefficients. |
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ISSN: | 0094-243X 1551-7616 |
DOI: | 10.1063/1.4907497 |