The R-convergence Rate of MDY Conjugate Gradient Method with Inexact Line Search for Unconstrained Optimization
作者单位：College of Humanities and Sciences of Northeast Normal University Department of Applied Mathematics and Mathematics Changchun University
会议名称：《第25届中国控制与决策会议》
主办单位：IEEE;NE Univ;IEEE Ind Elect Chapter;IEEE Harbin Sect Control Syst Soc Chapter;Guizhou Univ;IEEE Control Syst Soc;Syst Engn Soc China;Chinese Assoc Artificial Intelligence;Chinese Assoc Automat;Tech Comm Control Theory;Chinese Assoc Aeronaut;Automat Control Soc;Chinese Assoc Syst Simulat;Simulat Methods & Modeling Soc;Intelligent Control & Management Soc
会议日期：2013年
学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 07[理学] 070105[理学-运筹学与控制论] 0701[理学-数学]
基 金：supported by:The Founds of Jilin Province Science and Technology(NO.2013577 2013267 2013287)
关 键 词：Conjugate gradient method Unconstrained optimization problem R-convergence rate
摘 要：It is well-known that the Dai-Yuan conjugate gradient method. Recently, Zhang developed two modified Dai-Yuan （MDY） methods that are globally convergence if the standard Armijo line search is used. In this paper, firstly, we investigate the R-convergence rate of the MDY method with inexact Armijo line search. Secondly, We show another MVDY method convergence globally for nonconvex minimization problems. Thirdly, the MVDY method also have R- convergence rate with inexact Armijo line search. Numerical results show that this algorithm is effective in unconstrained optimization problems.