2020International Journal of Mathematical Modelling and Numerical OptimisationRequires access

A new efficient hybrid conjugate gradient method based on LS-DY-HS conjugate gradient parameter

Nirmalya Kumar Mohanty, Rupaj Kumar Nayak

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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.

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What this paper is about

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.

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Available 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.

Key concepts: Conjugate gradient method, Derivation of the conjugate gradient method, Nonlinear conjugate gradient method, Conjugate residual method, Conjugate, Line search, Gradient method, Biconjugate gradient method

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