关键词: 共轭梯度法, 正则化模型, Dai-Liao共轭参数,  , 充分下降性, 全局收敛性

Abstract: We gave a Dai-Liao conjugate gradient method based on regularization model. Firstly,  a new Dai-Liao parameter t was obtained by minimizing the 3-degree regularization model, and based  on this, an adaptive Dai-Liao parameter was generated according to  the properties of the  function near  the iterative point. Secondly, combined with improved Wolfe line search, we proposed a Dai-Liao conjugate gradient method based on regularization model. Finally, we proved that the search direction of the proposed 
method satisfied sufficient descent, and established the global convergence of the proposed algorithm under the general assumption. Numerical results show that the proposed algorithm is effective.

Key words: conjugate gradient method, regularization model,  , Dai-Liao conjugate parameter,  , sufficient descent, global convergence