In this paper, we have presented a numerical algorithm for the step-size estimation for minimization problems. Global convergence results are derived for descent algorithms in which the line search step is replaced by a step whose length is determined by step-size estimation formula. Numerical results show that the new estimation step-size required less storage and greatly speeded up the convergence of the gradient algorithm for large-scale unconstrained optimization problems. Also the new proposed algorithm seems to converge better and superior to other similar algorithms in many situations.
Y. AL-Bayati,A and Ivan Subhi Latif,A . (2009). A Modified estimation for the steplenght of a descent nonlinear algorithm . Kirkuk Journal of Science, 4(2), 94-107. doi: 10.32894/kujss.2009.39976
MLA
Y. AL-Bayati,A , and Ivan Subhi Latif,A . "A Modified estimation for the steplenght of a descent nonlinear algorithm ", Kirkuk Journal of Science, 4, 2, 2009, 94-107. doi: 10.32894/kujss.2009.39976
HARVARD
Y. AL-Bayati A, Ivan Subhi Latif A. (2009). 'A Modified estimation for the steplenght of a descent nonlinear algorithm ', Kirkuk Journal of Science, 4(2), pp. 94-107. doi: 10.32894/kujss.2009.39976
CHICAGO
A Y. AL-Bayati and A Ivan Subhi Latif, "A Modified estimation for the steplenght of a descent nonlinear algorithm ," Kirkuk Journal of Science, 4 2 (2009): 94-107, doi: 10.32894/kujss.2009.39976
VANCOUVER
Y. AL-Bayati A, Ivan Subhi Latif A. A Modified estimation for the steplenght of a descent nonlinear algorithm . Kirkuk J. Sci.. 2009;4(2):94-107. doi: 10.32894/kujss.2009.39976
