Descent property and global convergence of a new search direction method for unconstrained optimizationMethod for Unconstrained Optimization

Mohammed BELLOUFI; Rachid Benzine

Center of Academic Publications

Descent property and global convergence of a new search direction method for unconstrained optimizationMethod for Unconstrained Optimization

https://www.univ-soukahras.dz/en/publication/article/191

Mohammed BELLOUFI and Rachid Benzine (2014) Descent property and global convergence of a new search direction method for unconstrained optimizationMethod for Unconstrained Optimization. Numerical Functional Analysis and Optimization , 36(2), 169-180, Taylor & Francis Group

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Conjugate gradient methods are probably the most famous iterative methods for solving large scale optimization problems in scientific and engineering computation, characterized by the simplicity of their iteration and their low memory requirements. It is well known that the search direction plays a main role in the line search method. In this article, we propose a new search direction with the Wolfe line search technique for solving unconstrained optimization problems. Under the above line searches and some assumptions, the global convergence properties of the given methods are discussed. Numerical results and comparisons with other CG methods are given.

Item Type:	Journal
Divisions:	» Laboratory of Computer Science and Mathematics » Faculty of Science and Technology
ePrint ID:	191
Date Deposited:	2014-12-11
Further Information:	Google Scholar
URI:	https://www.univ-soukahras.dz/en/publication/article/191