In this paper a new class of self-scaling VM-algorithms for nonlinear optimization are investigated. Some theoretical results are given on the scaling strategies that guarantee the global and super linear convergence of the new proposed algorithms. Numerical evidence on thirty two well-known nonlinear test functions is generally encouraging.
Y. Al-Bayati and Maha S. Al-Salih,A . (2007). Global and Suplinear Convergent VM-Algorithms for nonlinear Optimization . Kirkuk Journal of Science, 2(2), 88-106. doi: 10.32894/kujss.2007.43440
MLA
Y. Al-Bayati and Maha S. Al-Salih,A . "Global and Suplinear Convergent VM-Algorithms for nonlinear Optimization ", Kirkuk Journal of Science, 2, 2, 2007, 88-106. doi: 10.32894/kujss.2007.43440
HARVARD
Y. Al-Bayati and Maha S. Al-Salih A. (2007). 'Global and Suplinear Convergent VM-Algorithms for nonlinear Optimization ', Kirkuk Journal of Science, 2(2), pp. 88-106. doi: 10.32894/kujss.2007.43440
CHICAGO
A Y. Al-Bayati and Maha S. Al-Salih, "Global and Suplinear Convergent VM-Algorithms for nonlinear Optimization ," Kirkuk Journal of Science, 2 2 (2007): 88-106, doi: 10.32894/kujss.2007.43440
VANCOUVER
Y. Al-Bayati and Maha S. Al-Salih A. Global and Suplinear Convergent VM-Algorithms for nonlinear Optimization . Kirkuk J. Sci.. 2007;2(2):88-106. doi: 10.32894/kujss.2007.43440
