吉林大学学报（理学版）2017，Vol.55Issue(4)：874-880,7.DOI:10.13413/j.cnki.jdxblxb.2017.04.18
一类充分下降共轭梯度法的全局收敛性
Global Convergence of a Class of Sufficient Descent Conjugate Gradient Methods
摘要
Abstract
The author presented a class of new conjugate gradient methods with conservative strategy in search direction.The global convergence results of these algorithms were obtained under the condition of general assumptions,and the numerical experiment results of these algorithms were given.The results show that the corresponding algorithms are sufficient descent in the case of the strong Wolfe inexact line search parameters σ<1/4,1/3,1/2,respectively.The new algorithm is suitable for solving large-scale unconstrained optimization problems.关键词
无约束优化/共轭梯度法/强Wolfe非精确线搜索/充分下降性/全局收敛性Key words
unconstrained optimization/conjugate gradient method/strong Wolfe inexact line search/sufficient descent property/global convergence分类
数理科学引用本文复制引用
林穗华..一类充分下降共轭梯度法的全局收敛性[J].吉林大学学报（理学版）,2017,55(4):874-880,7.基金项目
广西高校科研重点项目(批准号:ZD2014143)、 广西重点培育学科建设项目(批准号:桂教科研[2013]16)和广西民族师范学院科研项目(批准号:2013RCGG002). （批准号:ZD2014143）
