New Scale Dai-Yaun Conjugate Gradient Method for Unconstrained Optimization

Conjugate gradient algorithm is widely used for solving large-scale unconstrained optimization problems, because they do not need the storage of matrices. In this paper, we suggest a modified Dai-Yuan conjucay coefficient of conjugate gradient algorithm and propose new spectral form three-term conjugate gradient algorithm. These algorithms are used inexact line searches and Wolf line search conditions. These algorithms satisfied sufficient descent condition and the converge globally are provided under some assumptions. The numerical results indicate that the proposed algorithm is very effective and the new spectral algorithm is of very robust results depending on iterations and the number of known functions.