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Goldstein线搜索下混合共轭梯度法的全局收敛性
CONVERGENCE PROPERTIES OF A HYBRID CONJUGATE GRADIENT METHODS WITH GOLDSTEIN LINE SEARCH
【摘要】 本文结合FR算法和DY算法,给出了一类新的杂交共轭梯度算法,并结合Goldstein线搜索,在较弱的条件下证明了算法的收敛性.数值实验表明了新算法的有效性.
【Abstract】 In this paper, we propose a hybrid of conjugate gradient methods for unconstrained optimization based on Fletcher-Reeves Algorithm and Dai-Yuan Algorithm, which had taken the advantages of two Algorithms. The convergence of the new methods is proved with the Goldstein line search and without the descent condition . Numerical experiments show that the algorith is efficient.
【关键词】 无约束最优化;
非精确线搜索;
共轭梯度法;
全局收敛性;
【Key words】 Unconstrained optimization; Inexact line search; Hybrid conjugate gradient method; Global convergence;
【Key words】 Unconstrained optimization; Inexact line search; Hybrid conjugate gradient method; Global convergence;
【基金】 国家自然科学基金(60472071);北京市教委科研基金(KM200710028001)资助.
- 【文献出处】 计算数学 ,Mathematica Numerica Sinica , 编辑部邮箱 ,2007年02期
- 【分类号】O224
- 【被引频次】22
- 【下载频次】238