(北京科技大学 应用科学学院，北京 100083)
摘 要：共轭梯度法是求解无约束优化问题的一种重要的方法，尤其适用于大规模优化问题的求解。本文提出一族新的共轭梯度法，证明了其在推广的Wolfe非精确线搜索条件下具有全局收敛性。最后对算法进行了数值试验，试验结果验证了该算法的有效性。
关键词：运筹学；无约束优化；共轭梯度法；Wolfe线搜索；全局收敛性
中图分类号：O224 文章标识码：A 文章编号：1007-3221(2007)02-0065-04
Research into Global Convergence of a Class of Conjugate Gradient Methods
FAN Jian-fen, XIE Tie-jun, LIU Juan
(Applied Science School, UST Beijing, Beijing 100083, China)
Abstract:Conjugate gradient method is a method for solving nonlinear optimization problems,especially large-scale problems.In this paper a class of new conjugate gradient methods are presented,with which the global convergence with generalized Wolfe line search is proven.Finally, some numerical tests have been done and the results show that the algorithm is effective.
Key words:operations research; unconstrained optimization; conjugate gradient method; Wolfe line search; global convergence
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