Abstract

In this thesis aims to accelerate the convergence of classical conjugate gradient methods, we have proposed three algorithms based on this concept, where we specifically relied on a famous acceleration technique which is the hybridization of two algorithms, by convex combination of their coefficients that determine the different standard conjugate gradient methods.
After having proven the convergence of the proposed algorithms, using experimental functions, we have shown through numerical experiments that these algorithms are more efficient and perform than the combined algorithms.




Key words: Unconstrained optimization, Conjugate gradient method, Convex combination, Global convergence.

Information

Item Type:	Thesis
Divisions:	» Laboratory of Computer Science and Mathematics
ePrint ID:	2615
Date Deposited:	2021-06-28
Further Information:	Google Scholar
URI:	https://old.univ-soukahras.dz/en/publication/article/2615

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