On some studies a conjugate parameter plays an important role for the conjugate gradient methods. In this paper, a variant of hybrid is provided in the search direction based on the convex combination. This search direction ensures that the descent condition holds. The global convergence of the variant of hybrid is also obtained. Our strong evidence is a numerical analysis showing that the proposed variant of hybrid method is efficient than the Hestenes and Stiefel method
Conjugate gradient methods are very important ones for solving nonlinear optimization problems, espe...
AbstractConjugate gradient method is an important and efficient method to solve the unconstrained op...
In this paper, a new search direction vectors are defined for BFGS-CG proposed by Ibrahim et al. by ...
Hybridization is one of the popular approaches in modifying the conjugate gradient method. In this p...
In this paper, we proposed a new hybrid conjugate gradient algorithm for solving unconstrained optim...
In this paper, we propose a new hybrid conjugate gradient method for unconstrained optimization prob...
The nonlinear conjugate gradient algorithms are a very effective way in solving large-scale unconstr...
Taking advantage of the attractive features of Hestenes–Stiefel and Dai–Yuan conjugate gradient meth...
The conjugate gradient method an efficient technique for solving the unconstrained optimization prob...
The main work of this thesis is concerned with the comparison of conjugate gradient with hybrid conj...
In this study, we tend to propose a replacement hybrid algorithmic rule which mixes the search direc...
Many researchers are interested for developed and improved the conjugate gradient method for solving...
Hybridizing self-adjusting approach of Dong et al. and three-term formulation of Zhang et al., a non...
Conjugate gradient methods are widely used for unconstrained opti-mization, especially large scale p...
This paper contains two main parts, Part I and Part II, which discuss the local and global minimizat...
Conjugate gradient methods are very important ones for solving nonlinear optimization problems, espe...
AbstractConjugate gradient method is an important and efficient method to solve the unconstrained op...
In this paper, a new search direction vectors are defined for BFGS-CG proposed by Ibrahim et al. by ...
Hybridization is one of the popular approaches in modifying the conjugate gradient method. In this p...
In this paper, we proposed a new hybrid conjugate gradient algorithm for solving unconstrained optim...
In this paper, we propose a new hybrid conjugate gradient method for unconstrained optimization prob...
The nonlinear conjugate gradient algorithms are a very effective way in solving large-scale unconstr...
Taking advantage of the attractive features of Hestenes–Stiefel and Dai–Yuan conjugate gradient meth...
The conjugate gradient method an efficient technique for solving the unconstrained optimization prob...
The main work of this thesis is concerned with the comparison of conjugate gradient with hybrid conj...
In this study, we tend to propose a replacement hybrid algorithmic rule which mixes the search direc...
Many researchers are interested for developed and improved the conjugate gradient method for solving...
Hybridizing self-adjusting approach of Dong et al. and three-term formulation of Zhang et al., a non...
Conjugate gradient methods are widely used for unconstrained opti-mization, especially large scale p...
This paper contains two main parts, Part I and Part II, which discuss the local and global minimizat...
Conjugate gradient methods are very important ones for solving nonlinear optimization problems, espe...
AbstractConjugate gradient method is an important and efficient method to solve the unconstrained op...
In this paper, a new search direction vectors are defined for BFGS-CG proposed by Ibrahim et al. by ...