Quasi Newton Methods

Alemayu, Ataklti

dc.contributor.advisor	Guta, Berhanu
dc.contributor.author	Alemayu, Ataklti
dc.date.accessioned	2019-04-17T13:45:52Z
dc.date.available	2019-04-17T13:45:52Z
dc.date.issued	2018-06-07
dc.identifier.uri	http://etd.aau.edu.et/handle/123456789/18025
dc.description.abstract	In 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.	en_US
dc.language.iso	en	en_US
dc.publisher	Addis Ababa University	en_US
dc.subject	Convex Functions	en_US
dc.subject	Preliminaries	en_US
dc.title	Quasi Newton Methods	en_US
dc.type	Thesis	en_US