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JOURNALS // Vestnik Yuzhno-Ural'skogo Universiteta. Seriya Matematicheskoe Modelirovanie i Programmirovanie // Archive

Vestnik YuUrGU. Ser. Mat. Model. Progr., 2022 Volume 15, Issue 3, Pages 127–133 (Mi vyuru654)

Short Notes

A modification of Dai-Yuan's conjugate gradient algorithm for solving unconstrained optimization

Y. Najm Hudaa, I. Ahmed Hudab

a University of Duhok, Duhok, Kurdistan Region, Iraq
b University of Mosul, Mosul, Iraq

Abstract: The spectral conjugate gradient method is an essential generalization of the conjugate gradient method, and it is also one of the effective numerical methods to solve large scale unconstrained optimization problems. We propose a new spectral Dai–Yuan (SDY) conjugate gradient method to solve nonlinear unconstrained optimization problems. The proposed method's global convergence was achieved under appropriate conditions, performing numerical testing on 65 benchmark tests to determine the effectiveness of the proposed method in comparison to other methods like the AMDYN algorithm and some other existing ones like Dai-Yuan method.

Keywords: unconstrained optimization, conjugate gradient method, spectral conjugate gradient, sufficient descent, global convergence.

UDC: 519.6+517.972

MSC: 46N10, 65K10, 90C06

Received: 25.11.2021

Language: English

DOI: 10.14529/mmp220309



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