Solving Large Scale Nonlinear Optimization Programming via a Relatively Efficient Algorithm

In this work, we proposed a relatively efficient algorithm for solving the class of large scale optimization programming problem. In fact, we develop a primal dual algorithm which, it can be seen that, is efficient when the problem is really belongs to the class of large scale programming problems. It also can be seen that, the method is not expensive and can be coded easily into a convenient programming language

Keywords:

Large-scale optimization , interior point methods , nonlinear programming , constrained optimization , quasi-Newton methods