Abstract
In this article, we present a new hybrid conjugate gradient method for solving large Scale in unconstrained optimization problems. This method is a convex combination of Dai-Yuan conjugate gradient and Andrei- sufficient descent condition, satisfies the famous D-L conjugacy condition and in the same time solidarities with the newton direction with the suitable condition. The suggestion method always yields a descent search direction at each it iteration. Under strong wolfe powell(SWP) line search condition, the direction satisfy the global convergence of the proposed method is established. Finally, the results we achieved are good and it is show that our method is forceful and effective.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.