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     2026:7/2

International Journal of Multidisciplinary Research and Growth Evaluation

ISSN: (Print) | 2582-7138 (Online) | Impact Factor: 9.54 | Open Access

Convex combination of parameter CG Algorithms for Dai and Liao methods in Unconstrained Optimization

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Abstract

This paper studies the two – term conjugate gradient method for unconstrained optimization problem. Our idea is based on work scaled as convex combination of the Dai and Liao CG method. The conjugacy condition and global convergence for the proposed algorithms are satisfied under some assumptions. For our numerical results we have applied this algorithm this algorithm on the set of well-known test nonlinear functions in the unconstrained optimization.  

How to Cite This Article

Khalil K Abbo, Aynur J Namik (2025). Convex combination of parameter CG Algorithms for Dai and Liao methods in Unconstrained Optimization . International Journal of Multidisciplinary Research and Growth Evaluation (IJMRGE), 6(4), 1009-1013.

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