Abstract

A nonlinear conjugate gradient method solves unconstrained optimisation problem based on an efficient line search technique and maintains a decent direction search (in case of a minimisation problem) with the help of conjugate gradient parameter. In this paper, a new hybrid conjugate gradient method based on a hybrid conjugate gradient parameter βk is proposed. The proposed βk combines linearly the conjugate gradient parameters of LS, DY and HS method. The present work also discusses the global convergence of the modified algorithm with inexact line search. Moreover, the proposed method is tested on the unconstrained problems from the library CUTEr (Gould et al., 2015) and the results have been compared with the other state of the art algorithms. The results in the numerical experiment show that the proposed hybrid algorithm is efficient.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

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.