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  • 标题:A Line Search Algorithm for Unconstrained Optimization
  • 本地全文:下载
  • 作者:Gonglin Yuan ; Sha Lu ; Zengxin Wei
  • 期刊名称:Journal of Software Engineering and Applications
  • 印刷版ISSN:1945-3116
  • 电子版ISSN:1945-3124
  • 出版年度:2010
  • 卷号:3
  • 期号:5
  • 页码:503-509
  • DOI:10.4236/jsea.2010.35057
  • 出版社:Scientific Research Publishing
  • 摘要:It is well known that the line search methods play a very important role for optimization problems. In this paper a new line search method is proposed for solving unconstrained optimization. Under weak conditions, this method possesses global convergence and R-linear convergence for nonconvex function and convex function, respectively. Moreover, the given search direction has sufficiently descent property and belongs to a trust region without carrying out any line search rule. Numerical results show that the new method is effective.
  • 关键词:Line Search; Unconstrained Optimization; Global Convergence; R-linear Convergence
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