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A New Nonlinear Conjugate Gradient Method for Unconstrained Optimization Problems 被引量：1

A New Nonlinear Conjugate Gradient Method for Unconstrained Optimization Problems
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摘要 In this paper,an efficient conjugate gradient method is given to solve the general unconstrained optimization problems,which can guarantee the sufficient descent property and the global convergence with the strong Wolfe line search conditions.Numerical results show that the new method is efficient and stationary by comparing with PRP＋ method,so it can be widely used in scientific computation.
作者 LIU Jin-kui WANG Kai-rong SONG Xiao-qian DU Xiang-lin
机构地区 College of Mathematics and Computer Science College of Mathematics and Physics
出处 《Chinese Quarterly Journal of Mathematics》 CSCD 2010年第3期444-450,共7页 数学季刊（英文版）
基金 Supported by the Fund of Chongqing Education Committee(KJ091104)
关键词 unconstrained optimization conjugate gradient method strong Wolfe line search sufficient descent property global convergence 非强迫的优化；结合坡度方法；强壮的沃尔夫线搜索；足够的降下性质；全球集中；
分类号 O221.2 [理学—运筹学与控制论]
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参考文献11

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二级参考文献2

共引文献9

同被引文献11

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Chinese Quarterly Journal of Mathematics
2010年 第3期

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