The nonlinear conjugate gradient method is widely used to solve unconstrained optimization problems. In this paper the development of different versions of nonlinear conjugate gradient methods with global convergence properties proved. Numerical results indicated that the proposed method is very efficient
Hybrid conjugate gradient-steepest descent algorithms for unconstrained minimizatio
In this paper, a new conjugate gradient method is proposed for large-scale unconstrained o...
Some problems have no analytical solution or too difficult to solve by scientists, engineers, and ma...
A modified spectral methods for solving unconstrained optimization problems based on the formulae ar...
V této práci studujeme nelineární metody sdružených gradientů pro nepodmíněnou optimalizaci. Uvádíme...
In the following manuscript we will show as a starting point a theoretical analysis of the gradient ...
AbstractIn this paper we develop a new class of conjugate gradient methods for unconstrained optimiz...
Conjugate gradient methods are effective in solving linear equations and solving non-linear optimiza...
A detailed description of numerical methods for unconstrained minimization is presented. This first ...
In this paper we study new preconditioners for the Nonlinear Conjugate Gradient (NCG) method in larg...
Conjugate Gradient (CG) methods are widely used for solving unconstrained optimization problems. The...
AbstractThis letter presents a scaled memoryless BFGS preconditioned conjugate gradient algorithm fo...
In this paper, We propose a new nonlinear conjugate gradient method (FRA) that satisfies a sufficien...
The conjugate gradient method provides a very powerful tool for solving unconstrained optimization p...
AbstractFor solving large-scale unconstrained minimization problems, the nonlinear conjugate gradien...
Hybrid conjugate gradient-steepest descent algorithms for unconstrained minimizatio
In this paper, a new conjugate gradient method is proposed for large-scale unconstrained o...
Some problems have no analytical solution or too difficult to solve by scientists, engineers, and ma...
A modified spectral methods for solving unconstrained optimization problems based on the formulae ar...
V této práci studujeme nelineární metody sdružených gradientů pro nepodmíněnou optimalizaci. Uvádíme...
In the following manuscript we will show as a starting point a theoretical analysis of the gradient ...
AbstractIn this paper we develop a new class of conjugate gradient methods for unconstrained optimiz...
Conjugate gradient methods are effective in solving linear equations and solving non-linear optimiza...
A detailed description of numerical methods for unconstrained minimization is presented. This first ...
In this paper we study new preconditioners for the Nonlinear Conjugate Gradient (NCG) method in larg...
Conjugate Gradient (CG) methods are widely used for solving unconstrained optimization problems. The...
AbstractThis letter presents a scaled memoryless BFGS preconditioned conjugate gradient algorithm fo...
In this paper, We propose a new nonlinear conjugate gradient method (FRA) that satisfies a sufficien...
The conjugate gradient method provides a very powerful tool for solving unconstrained optimization p...
AbstractFor solving large-scale unconstrained minimization problems, the nonlinear conjugate gradien...
Hybrid conjugate gradient-steepest descent algorithms for unconstrained minimizatio
In this paper, a new conjugate gradient method is proposed for large-scale unconstrained o...
Some problems have no analytical solution or too difficult to solve by scientists, engineers, and ma...