GLOBAL CONVERGENCE OF THE TMR METHOD FOR UNCONSTRAINED OPTIMIZATION PROBLEMS

T. BOUALI; M. BELLOUFI; R. GUEFAIFIA

Title	GLOBAL CONVERGENCE OF THE TMR METHOD FOR UNCONSTRAINED OPTIMIZATION PROBLEMS
Publication Type	Journal Article
Year of Publication	2017
Authors	BOUALI, T, BELLOUFI, M, GUEFAIFIA, R
Secondary Title	Communications in Applied Analysis
Volume	21
Issue	1
Start Page	15
Pagination	15
Date Published	01/2017
Type of Work	scientific: mathematics
ISSN	1083-2564
AMS	65H10, 90C26
Abstract	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 paper, 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 result shows that the proposed formula is superior and more efficient when compared to other CG coefficients.
URL	http://www.acadsol.eu/en/articles/21/1/2.pdf
DOI	10.12732/caa.v21i1.2
Short Title	TMR Method for Optimization Problems
Alternate Journal	CAA
Refereed Designation	Refereed
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