Global Convergence Properties of A New Conjugate Gradient Method for Unconstrained Optimization

摘要：

A new conjugate gradient method for solving unconstrained optimization problems is proposed, and which has the sufficient descent property with the strong Wolfe line search. Under the exact line search and the strong Wolfe Powell line search, the global convergence properties of the given method are discussed respectively. The numerical results show that this method is promising for the given test problems from 8.

关键词： Unconstrained optimization Conjugate gradient method Strong Wolfe line search Global convergence

作者: Jin-kui Liu Fei-xiang Chen Jun-ming Li

作者单位: Chongqing Three Gorges University College of Mathematics and Computer Science Wanzhou, Chongqing, Ch Guangxi University of Technology Liuzhou, Guangxi, China

会议类型: 国际会议

会议名称: 2010 International Conference on Information Security and Artificial Intelligence(2010年信息安全与人工智能国际会议 ISAI 2010)

会议地点: 成都

会议语种:英文

页码: 1126-1129

在线出版日期: 2010-12-17（万方平台首次上网日期，不代表论文的发表时间）