Problems of sciences concerned with minimizing an objective function that depends on real
values without restrictions on there is called unconstrained optimization problems. Quasi …

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 …

In this study, we develop a different parameter of three term conjugate gradient kind, this
scheme depends principally on pure conjugacy condition (PCC), Whereas, the conjugacy …

The paper surveys, classifies and investigates theoretically and numerically main classes of
line search methods for unconstrained optimization. Quasi-Newton (QN) and conjugate …

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 …

The nonlinear conjugate gradient method is an effective technique for solving large-scale
minimizations problems, and has a wide range of applications in various fields, such as …

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 …

The Secant equation has long been the foundation of quasi-Newton methods, as updated
Hessian approximations satisfy the equation with each iteration. Several publications have …

The quasi-Newton equation is the very foundation of an assortment of the quasi-Newton
methods for optimization minimization problem. In this paper, we deriving a new quasi …