A modified Polak-Ribiere-Polyak descent method for unconstrained optimization

被引：3
|
作者：
Qu, Aiping [1 ,2 ]
Li, Min [2 ]
Xiao, Yue [3 ]
Liu, Juan [1 ]
机构：
[1] Wuhan Univ, Sch Comp, Wuhan 430072, Peoples R China
[2] Huaihua Univ, Dept Math, Huaihua 418000, Peoples R China
[3] Huaihua Univ, Int Off, Huaihua 418000, Peoples R China
来源：
OPTIMIZATION METHODS & SOFTWARE | 2014年 / 29卷 / 01期
关键词：
unconstrained optimization; conjugate gradient method; sufficient descent property; global convergence; CONJUGATE-GRADIENT METHODS;
D O I：
10.1080/10556788.2012.755182
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
In this paper, a modified Polak-Ribiere-Polyak (MPRP) conjugate gradient method for smooth unconstrained optimization is proposed. This method produces at each iteration a descent direction, and this property is independent of the line search adopted. Under standard assumptions, we prove that the MPRP method using strong Wolfe conditions is globally convergent. The results of computational experiments are reported and show the effectiveness of the proposed method.
引用
收藏
页码：177 / 188
页数：12
相关论文
共 50 条
  • [41] A three-term Polak-Ribiere-Polyak derivative-free method and its application to image restoration
    Ibrahim, Abdulkarim Hassan
    Deepho, Jitsupa
    Abubakar, Auwal Bala
    Adamu, Abubakar
    SCIENTIFIC AFRICAN, 2021, 13
  • [42] A Note on the Global Convergence of the Quadratic Hybridization of Polak-Ribiere-Polyak and Fletcher-Reeves Conjugate Gradient Methods
    Babaie-Kafaki, Saman
    JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS, 2013, 157 (01) : 297 - 298
  • [43] A Polak-Ribiere-Polyak Conjugate Gradient-Based Neuro-Fuzzy Network and Its Convergence
    Gao, Tao
    Wang, Jian
    Zhang, Bingjie
    Zhang, Huaqing
    Ren, Peng
    Pal, Nikhil R.
    IEEE ACCESS, 2018, 6 : 41551 - 41565
  • [44] A three-terms Polak-Ribiere-Polyak conjugate gradient algorithm for large-scale nonlinear equations
    Yuan, Gonglin
    Zhang, Maojun
    JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS, 2015, 286 : 186 - 195
  • [45] The global convergence of the Polak-Ribiere-Polyak conjugate gradient algorithm under inexact line search for nonconvex functions
    Yuan, Gonglin
    Wei, Zengxin
    Yang, Yuning
    JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS, 2019, 362 : 262 - 275
  • [46] Fast control parameterization optimal control with improved Polak-Ribiere-Polyak conjugate gradient implementation for industrial dynamic processes
    Liu, Ping
    Hu, Qingquan
    Li, Lei
    Liu, Mingjie
    Chen, Xiaolei
    Piao, Changhao
    Liu, Xinggao
    ISA TRANSACTIONS, 2022, 123 : 188 - 199
  • [47] A modified nonlinear Polak–Ribière–Polyak conjugate gradient method with sufficient descent property
    Xiaoliang Dong
    Calcolo, 2020, 57
  • [48] A descent extension of a modified Polak–Ribière–Polyak method with application in image restoration problem
    Saman Babaie-Kafaki
    Nasrin Mirhoseini
    Zohre Aminifard
    Optimization Letters, 2023, 17 : 351 - 367
  • [49] A Polak-Ribiere-Polyak Conjugate Gradient Algorithm Optimized Broad Learning System for Lithium-ion Battery State of Health Estimation
    Gu, Tianyu
    Wang, Dongqing
    Li, Yuxiang
    JOURNAL OF THE ELECTROCHEMICAL SOCIETY, 2022, 169 (09)
  • [50] A modified CG-DESCENT method for unconstrained optimization
    Dai, Zhifeng
    Wen, Fenghua
    JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS, 2011, 235 (11) : 3332 - 3341
12345