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., & 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
Abbas Y. AL-Bayati; and 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
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
VANCOUVER
Y. AL-Bayati, A., Ivan Subhi Latif, A. A Modified estimation for the steplenght of a descent nonlinear algorithm. Kirkuk Journal of Science, 2009; 4(2): 94-107. doi: 10.32894/kujss.2009.39976
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