in this work we develop a new optimal without memory class for approximating a simple root of a nonlinear equation. this class includes three parameters. therefore, we try to derive some with memory methods so that the convergence order increases as high as possible. some numerical examples are also ‎presented.‎‎

‎‎‎in this paper‎, ‎we develop multi-step methods to solve a class of two-dimensional nonlinear volterra integral equations (2d-nvies) of the first kind‎. ‎here‎, ‎we convert a 2d-nvie of the first kind to a one-dimensional linear vie of the first kind and then we solve the resulted equation numerically by multi-step methods‎. ‎we also verify convergence and error analysis of the method‎. ‎at t...

Iterative methods which have high convergence order are crucial in computational mathematics since the iterates produce sequences converging to root of a non-linear equation. A plethora applications chemistry and physics require solution equations abstract spaces iteratively. The derivation iterative requires expansions using Taylor series formula higher-order derivatives not present method. Th...

For solving non-smooth multidimensional optimization problems, we present a family of relaxation subgradient methods (RSMs) with built-in algorithm for finding the descent direction that forms an acute angle all subgradients in neighborhood current minimum. Minimizing function along opposite (with minus sign) enables to go beyond The algorithms is based on systems inequalities. finite convergen...