AbstractWe propose a new monotone algorithm for unconstrained optimization in the frame of Barzilai and Borwein (BB) method and analyze the convergence properties of this new descent method. Motivated by the fact that BB method does not guarantee descent in the objective function at each iteration, but performs better than the steepest descent method, we therefore attempt to find stepsize formula which enables us to approximate the Hessian based on the Quasi-Cauchy equation and possess monotone property in each iteration. Practical insights on the effectiveness of the proposed techniques are given by a numerical comparison with the BB method
In this paper, we propose a new non-monotone conjugate gradient method for solving unconstrained non...
In a recent paper, Barzilai and Borwein presented a new choice of steplength for the gradient method...
The focus of this thesis is on finding the unconstrained minimizer of a function by using the alter...
We propose a new monotone algorithm for unconstrained optimization in the frame of Barzilai and Borw...
AbstractWe propose a new monotone algorithm for unconstrained optimization in the frame of Barzilai ...
In this paper we present a new algorithm of steepest descent type. A new technique for steplength co...
AbstractIn this paper, we propose some improvements on a new gradient-type method for solving large-...
The focus of this thesis is on finding the unconstrained minimizer of a function. Specifically, we ...
In this paper, we propose some improvements on a new gradient-type method for solving large-scale un...
The negative gradient direction to find local minimizers has been associated with the classical stee...
ABSTRACT In this paper we propose new globalization strategies for the Barzilai and Borwein gradient...
In this work we develop a new gradient-type method with improved Hessian approximation for unconstra...
The focus of the thesis is on finding the unconstrained minimizer of a function by using the fixed s...
Many methods for solving minimization problems are variants of Newton method, which requires the spe...
The Barzilai–Borwein (BB) gradient method is favourable over the classical steepest descent method b...
In this paper, we propose a new non-monotone conjugate gradient method for solving unconstrained non...
In a recent paper, Barzilai and Borwein presented a new choice of steplength for the gradient method...
The focus of this thesis is on finding the unconstrained minimizer of a function by using the alter...
We propose a new monotone algorithm for unconstrained optimization in the frame of Barzilai and Borw...
AbstractWe propose a new monotone algorithm for unconstrained optimization in the frame of Barzilai ...
In this paper we present a new algorithm of steepest descent type. A new technique for steplength co...
AbstractIn this paper, we propose some improvements on a new gradient-type method for solving large-...
The focus of this thesis is on finding the unconstrained minimizer of a function. Specifically, we ...
In this paper, we propose some improvements on a new gradient-type method for solving large-scale un...
The negative gradient direction to find local minimizers has been associated with the classical stee...
ABSTRACT In this paper we propose new globalization strategies for the Barzilai and Borwein gradient...
In this work we develop a new gradient-type method with improved Hessian approximation for unconstra...
The focus of the thesis is on finding the unconstrained minimizer of a function by using the fixed s...
Many methods for solving minimization problems are variants of Newton method, which requires the spe...
The Barzilai–Borwein (BB) gradient method is favourable over the classical steepest descent method b...
In this paper, we propose a new non-monotone conjugate gradient method for solving unconstrained non...
In a recent paper, Barzilai and Borwein presented a new choice of steplength for the gradient method...
The focus of this thesis is on finding the unconstrained minimizer of a function by using the alter...