Show simple item record

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


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search AAU-ETD


Browse

My Account