QUASI NEWTON MULTI STEP n/4 SKIPPING TECHNIQUE FOR OPTIMIZATION OF UNCONSTRAINED NONLINEAR PROBLEMS

Abstract

Ford and Moghrabi [2] introduced the multi-step quasi-Newton method for optimization, Where Hessian matrix is updated for each iteration, this make it computationally expensive. To overcome this problem Jhon and Nudrat [4] introduced a multi-step skipping technique, which shows a better experimental results. In Ford and Moghrabi, papers series, they introduced some techniques (Accumulative and Fixed-point approaches) to describe the parametric values needed to figure out the distances between many sets of iterations being involved in the recent interpolation curve.

In this thesis, we extended the existing three-step Fixed-point skipping approach and examine the sensitivity of this technique. Evidently, experimental result provides, positive improvement with comparison to standard Broyden-Fletcher-GoldfrabShanno (BFGS) method. Result shows comparatively, three-step Fixed-point skipping technique computational saves time than existing single-step BFGS method