数学

一类具有充分下降性的共轭梯度算法

  • 徐晓光 ,
  • 王开荣
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  • 重庆大学 数学与统计学院, 重庆 401331
徐晓光,男,硕士研究生,研究方向为最优化理论、算法及应用.E-mail:xxgcqu@163.com

收稿日期: 2016-05-16

  网络出版日期: 2017-03-23

基金资助

重庆市研究生教育教学改革研究项目(yjg143046)

A class of conjugate gradient algorithm with sufficient descent property

  • XU Xiao-guang ,
  • WANG Kai-rong
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  • College of Mathematics and Statistics, Chongqing University, Chongqing 401331, China

Received date: 2016-05-16

  Online published: 2017-03-23

摘要

在一些著名的共轭梯度算法基础之上,提出一类新的共轭梯度算法,用于求解无约束优化问题.该方法在不依赖于任何线搜索的情况下能够保证充分下降性,且在Wolfe线搜索下证明了算法具有全局收敛性.数值结果表明新提出的算法是有效的.

本文引用格式

徐晓光 , 王开荣 . 一类具有充分下降性的共轭梯度算法[J]. 华东师范大学学报(自然科学版), 2017 , 2017(2) : 44 -51,60 . DOI: 10.3969/j.issn.1000-5641.2017.02.006

Abstract

On the basis of some famous conjugate gradient algorithms, a class of new nonlinear conjugate gradient algorithm is proposed for solving unconstrained optimization problems, which can generate sufficient descent directions at each iteration regardless of any line search. Under the Wolfe line searches, the global convergence of the proposed algorithm is proved. Numerical experiment results show that the proposed method is promising.

参考文献

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