A new hybrid conjugate gradient method of unconstrained optimization methods

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dc.contributor.authorChenna Nasreddine
dc.contributor.authorBadreddine Sellami
dc.contributor.authorBelloufi Mohammed
dc.date.accessioned2023-09-17T10:48:52Z
dc.date.available2023-09-17T10:48:52Z
dc.date.issued2022
dc.description.abstractIn this paper, we present a new hybrid method to solve a nonlinear unconstrained optimization problem by using conjugate gradient, which is a convex combination of Liu–Storey (LS) conjugate gradient method and Hager–Zhang (HZ) conjugate gradient method. This method possesses the sufficient descent property with Strong Wolfe line search and the global convergence with the strong Wolfe line search. In the end of this paper, we illustrate our method by giving some numerical examples.
dc.identifier.issn10.1142/S179355712250070X
dc.identifier.urihttps://dspace.univ-soukahras.dz/handle/123456789/1776
dc.language.isoen
dc.publisherAsian-European Journal of Mathematics
dc.relation.ispartofseries10.1142/S179355712250070X
dc.titleA new hybrid conjugate gradient method of unconstrained optimization methods
dc.typeArticle

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