Conjugate Gradient (CG) method is one of the popular methods that solve the large- scale unconstrained optimization problems, because they do not need the storage of matrices. In this paper, we are particularly interested in three-term conjugate gradient methods. We are using only classical parameter on this paper. In this paper, we are using exact line search. These methods have been tested using only the selected optimization test function with different initial point from the nearest to the solution point to the furthest from the solution point. The result is analysed based on the number of the iteration and CPU time. Based on the result, Narushima et al. is the best method of all in term of both number of iteration and CPU times
Abstract Conjugate gradient (CG) methods have been practically used to solve large-scale unconstrain...
In this paper, a new conjugate gradient method is proposed for large-scale unconstrained o...
The conjugate gradient (CG) method has played a special role in solving large-scale nonlinear optimi...
The conjugate gradient (CG) method is a method to solve unconstrained optimization problems. Moreove...
Conjugate gradient (CG) methods have been widely used as schemes to solve large-scale unconstrained ...
Abstract The nonlinear conjugate gradient (CG) algorithm is a very effective method for optimization...
Two modified three-term type conjugate gradient algorithms which satisfy both the descent condition ...
In this study, we develop a different parameter of three term conjugate gradient kind, this scheme d...
The nonlinear conjugate gradient (CG) method is essential in solving large-scale unconstrained optim...
Conjugate gradient methods are widely used for solving large-scale unconstrained optimization proble...
The conjugate gradient method provides a very powerful tool for solving unconstrained optimization p...
One of the open problems known to researchers on the application of nonlinear conjugate gradient met...
This paper further studies the WYL conjugate gradient (CG) formula with βkWYL≥0 and presents a three...
In this paper, a new formula of is suggested for the conjugate gradient method of solving unconstra...
This work suggests several multi-step three-term Conjugate Gradient (CG)- algorithms that satisfies ...
Abstract Conjugate gradient (CG) methods have been practically used to solve large-scale unconstrain...
In this paper, a new conjugate gradient method is proposed for large-scale unconstrained o...
The conjugate gradient (CG) method has played a special role in solving large-scale nonlinear optimi...
The conjugate gradient (CG) method is a method to solve unconstrained optimization problems. Moreove...
Conjugate gradient (CG) methods have been widely used as schemes to solve large-scale unconstrained ...
Abstract The nonlinear conjugate gradient (CG) algorithm is a very effective method for optimization...
Two modified three-term type conjugate gradient algorithms which satisfy both the descent condition ...
In this study, we develop a different parameter of three term conjugate gradient kind, this scheme d...
The nonlinear conjugate gradient (CG) method is essential in solving large-scale unconstrained optim...
Conjugate gradient methods are widely used for solving large-scale unconstrained optimization proble...
The conjugate gradient method provides a very powerful tool for solving unconstrained optimization p...
One of the open problems known to researchers on the application of nonlinear conjugate gradient met...
This paper further studies the WYL conjugate gradient (CG) formula with βkWYL≥0 and presents a three...
In this paper, a new formula of is suggested for the conjugate gradient method of solving unconstra...
This work suggests several multi-step three-term Conjugate Gradient (CG)- algorithms that satisfies ...
Abstract Conjugate gradient (CG) methods have been practically used to solve large-scale unconstrain...
In this paper, a new conjugate gradient method is proposed for large-scale unconstrained o...
The conjugate gradient (CG) method has played a special role in solving large-scale nonlinear optimi...