Guta, BerhanuAlemayu, Ataklti2019-04-172023-11-092019-04-172023-11-092018-06-07http://10.90.10.223:4000/handle/123456789/18025In this work, we investigate quasi Newton methods for solving unconstrained optimization problems. We consider two di erent quasi-Newton update formulas, namely, Broyden- Fletcher-Goldfarb and shanno (BFGS) update and Davidon-Fletcher-powell (DFP) up- date. Line search method is used to nd the step length at each iteration. The methods are tested on seven benchmark probelems and comparisons are made among Newton's method, quasi-Newton methods (BFGS and DFP updates) and steepest descent method. Also comparisons are made between the quasi-Newton methods (BFGS and DFP up- dates). Finally conclusions are drawn upon the obtained results.enConvex FunctionsPreliminariesQuasi Newton MethodsThesis