数学物理学报 ›› 2022, Vol. 42 ›› Issue (1): 216-227.

• 论文 • 上一篇    下一篇

一个带重启步的改进PRP型谱共轭梯度法

江羡珍(),廖伟(),简金宝*(),毋晓迪()   

  1. 广西民族大学数学与物理学院, 应用数学与人工智能研究中心 & 广西混杂计算与集成电路设计分析重点实验室 南宁 530006
  • 收稿日期:2021-01-18 出版日期:2022-02-26 发布日期:2022-02-23
  • 通讯作者: 简金宝 E-mail:yl2811280@163.com;1436134351@qq.com;jianjb@gxu.edu.cn;1710703068@qq.com
  • 作者简介:江羡珍, E-mail: yl2811280@163.com|廖伟, E-mail: 1436134351@qq.com|毋晓迪, E-mail: 1710703068@qq.com
  • 基金资助:
    广西自然科学基金(2020GXNSFDA238017);广西自然科学基金(2018GXNSFAA281099);广西民族大学科研基金(2018KJQD02);广西民族大学研究生创新项目(gxun-chxp201909)

An Improved PRP Type Spectral Conjugate Gradient Method with Restart Steps

Xianzhen Jiang(),Wei Liao(),Jinbao Jian*(),Xiaodi Wu()   

  1. Center for Applied Mathematics and Artificial Intelligence & Guangxi Key Laboratory of Hybrid Compution and IC Design Analysis, College of Mathematics and Physics, Guangxi University for Nationalities, Nanning 530006
  • Received:2021-01-18 Online:2022-02-26 Published:2022-02-23
  • Contact: Jinbao Jian E-mail:yl2811280@163.com;1436134351@qq.com;jianjb@gxu.edu.cn;1710703068@qq.com
  • Supported by:
    the NSF of Guangxi Province(2020GXNSFDA238017);the NSF of Guangxi Province(2018GXNSFAA281099);the Research Project of Guangxi University for Nationalities(2018KJQD02);the Innovation Project of Guangxi University for Nationalities Graduate Education(gxun-chxp201909)

摘要:

Polak-Ribière-Polak(PRP)方法是经典共轭梯度法中数值表现较好的方法之一.结合Wolfe非精确线搜索准则对PRP公式进行改进,从而产生新的共轭参数,并基于新共轭参数设计新的谱参数,引入重启条件并构造新的重启方向,进而建立一个带重启步的谱共轭梯度算法.在常规假设及强Wolfe非精确线搜索步长准则下,算法具有充分下降性和全局收敛性.最后,对算法进行中大规模数值实验并与当前公认数值效果较好的同类方法进行比较,结果表明新算法是很有效的.

关键词: 无约束优化, 谱共轭梯度法, 重启方向, 强Wolfe线搜索

Abstract:

The Polak-Ribière-Polak algorithm is considered one of the most efficient methods among classical conjugate gradient methods (CGMs). To generate new conjugate parameter, an improved PRP formula is proposed by combining the strong Wolfe line search condition. Furthermore, a new spectral parameter and a new restart direction are designed, and thus a new spectral conjugate gradient method with restart steps is established. Using the strong Wolfe line search condition to yield the step length, the sufficient descent property and global convergence of the new algorithm are obtained under the general assumptions. Finally, for the proposed algorithm, a medium-large scale numerical experiments is performed, and compared with some existing efficient CGMs, the numerical results show that the proposed algorithm is very promising.

Key words: Unconstrained optimization, Spectral conjugate gradient method, Restart direction, Strong Wolfe line search

中图分类号: 

  • O221