Quasi-Newton methods are a class of numerical methods for solving the problem of
unconstrained optimization. To improve the overall efficiency of resulting algorithms, we use …

The conjugate gradient methods are noted to be exceedingly valuable for solving large-
scale unconstrained optimization problems since it needn't the storage of matrices. Mostly …

The focus for quasi-Newton methods is the quasi-Newton equation. A new quasi-Newton
equation is derived for quadratic function. Then, based on this new quasi-Newton equation …

Quasi-Newton method is an efficient method for solving unconstrained optimization
problems. Self-scaling is one of the common approaches in the modification of the quasi …

The quasi-Newton equation is the very foundation of an assortment of the quasi-Newton
methods. In this paper, we derive a new quasi-Newton equation with a gradient-difference …

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 …

In this research, we developed the Newton method to diminish the number of iterations to
arrive at the optimal solution for the problem, depending on the Taylor series to approximate …

One simple and well known method for minimizing the functions is a spectral conjugate
gradient method. In this paper, we derive a new spectral on the method of gradient, which …

In this article, a modified BFGS method is introduced based on an innovative quasi-Newton
type equation built on the quadratic model. An important property of the introduced method …

Quasi-Newton methods are one of the popular iterative schemes to solve unconstrained
optimization problems. The basic idea of the quasi-Newton method is to update successively …