Add to ORKGIn this paper we present a new line search method known as the HBFGS method, which uses the search direction of the conjugate gradient method with the quasi-Newton updates. The Broyden-Fletcher-Goldfarb-Shanno (BFGS) update is used as approximation of the Hessian for the methods. The new algorithm is compared with the BFGS method in terms of iteration counts and CPU-time. Our numerical analysis provides strong evidence that the proposed HBFGS method is more efficient than the ordinary BFGS method. Besides, we also prove that the new algorithm is globally convergent
In this article, a class of nonconvex unconstrained optimization problems is considered. As the Armi...
summary:Simple modifications of the limited-memory BFGS method (L-BFGS) for large scale unconstraine...
Non-asymptotic analysis of quasi-Newton methods have gained traction recently. In particular, severa...
In this paper we present a new line search method known as the HBFGS method, which uses the search d...
In this paper we present a new search direction known as the CG-BFGS method, which uses the search d...
Among the quasi-Newton algorithms, the BFGS method is often discussed by related scholars. However, ...
In solving large scale problems, the quasi-Newton method is known as the most efficient method in so...
A new hybrid quasi-Newton search direction ( ) is proposed. It uses the update formula of Broyden–F...
The BFGS method is one of the most efficient quasi-Newton methods for solving small- and medium-size...
In this paper, we seek the conjugate gradient direction closest to the direction of the scaled memor...
The BFGS method is one of the most effective quasi-Newton algorithms for minimization-optimization p...
AbstractConjugate gradient methods are conjugate direction or gradient deflection methods which lie ...
In this work we propose and analyze a hybrid conjugate gradient (CG) method in which the parameter β...
In this paper, a new search direction vectors are defined for BFGS-CG proposed by Ibrahim et al. by ...
This paper is concerned with the open problem whether BFGS method with inexact line search converges...
In this article, a class of nonconvex unconstrained optimization problems is considered. As the Armi...
summary:Simple modifications of the limited-memory BFGS method (L-BFGS) for large scale unconstraine...
Non-asymptotic analysis of quasi-Newton methods have gained traction recently. In particular, severa...
In this paper we present a new line search method known as the HBFGS method, which uses the search d...
In this paper we present a new search direction known as the CG-BFGS method, which uses the search d...
Among the quasi-Newton algorithms, the BFGS method is often discussed by related scholars. However, ...
In solving large scale problems, the quasi-Newton method is known as the most efficient method in so...
A new hybrid quasi-Newton search direction ( ) is proposed. It uses the update formula of Broyden–F...
The BFGS method is one of the most efficient quasi-Newton methods for solving small- and medium-size...
In this paper, we seek the conjugate gradient direction closest to the direction of the scaled memor...
The BFGS method is one of the most effective quasi-Newton algorithms for minimization-optimization p...
AbstractConjugate gradient methods are conjugate direction or gradient deflection methods which lie ...
In this work we propose and analyze a hybrid conjugate gradient (CG) method in which the parameter β...
In this paper, a new search direction vectors are defined for BFGS-CG proposed by Ibrahim et al. by ...
This paper is concerned with the open problem whether BFGS method with inexact line search converges...
In this article, a class of nonconvex unconstrained optimization problems is considered. As the Armi...
summary:Simple modifications of the limited-memory BFGS method (L-BFGS) for large scale unconstraine...
Non-asymptotic analysis of quasi-Newton methods have gained traction recently. In particular, severa...