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所属单位：

中南大学

发表刊物：

OPTIMIZATION

项目来源：

Natural Science Foundation of Hunan Province 14JJ2003 13JJ3002 National Natural Science Foundati

关键字：

algorithms; optimization; conjugate gradient method; global convergence

摘要：

In this article, we present an improved three-term conjugate gradient algorithm for large-scale unconstrained optimization. The search directions in the developed algorithm are proved to satisfy an approximate secant equation as well as the Dai-Liao's conjugacy condition. With the standard Wolfe line search and the restart strategy, global convergence of the algorithm is established under mild conditions. By implementing the algorithm to solve 75 benchmark test problems with dimensions from 1000 to 10,000, the obtained numerical results indicate that the algorithm outperforms the state-of-the-

合写作者：

Zhong Wan

第一作者：

Songhai Deng

论文类型：

基础研究

文献类型：

J

卷号：

64

期号：

12

页面范围：

2679-2691

ISSN号：

0233-1934

是否译文：

否

发表时间：

2015-12-01