Title : ( Two Adaptive Dai–Liao Nonlinear Conjugate Gradient Methods )
Authors: Saman Babaie-Kafaki , Reza Ghanbari ,
دانلود فایل برای اعضای دانشگاهAccess to full-text not allowed by authors
Abstract
Following recent attempts to find appropriate choices for parameter of the nonlinear conjugate gradient method proposed by Dai and Liao, two adaptive versions of the method are proposed based on a matrix analysis and using the memoryless BFGS updating formula. Under proper conditions, it is shown that the methods are globally convergent. Numerical experiments are done on a set of CUTEr unconstrained optimization test problems; they demonstrate the efficiency of the proposed methods in the sense of Dolan–Moré performance profile.
Keywords
, Unconstrained optimization, Conjugate gradient method, BFGS update, Line search, Global convergence
@article{paperid:1066987,
author = {Saman Babaie-Kafaki and Ghanbari, Reza},
title = {Two Adaptive Dai–Liao Nonlinear Conjugate Gradient Methods},
journal = {Iranian Journal of Science and Technology-Transaction A: Science},
year = {2017},
volume = {42},
number = {3},
month = {January},
issn = {1028-6276},
pages = {1505--1509},
numpages = {4},
keywords = {Unconstrained optimization; Conjugate gradient method; BFGS update; Line search; Global convergence},
}
%0 Journal Article
%T Two Adaptive Dai–Liao Nonlinear Conjugate Gradient Methods
%A Saman Babaie-Kafaki
%A Ghanbari, Reza
%J Iranian Journal of Science and Technology-Transaction A: Science
%@ 1028-6276
%D 2017
