Modification of steepest descent method for solving unconstrained optimization

Abstract

The classical steepest descent (SD) method is known as one of the earliest and the best method to minimize a function. Even though the convergence rate is quite slow, but its simplicity has made it one of the easiest methods to be used and applied especial! in the form of computer codes. In this research, a new modification of SD method is proposed using a new search direction (dk) in the form of two parameters. The numerical result based on number of iteration and CPU time using standard optimization test problems shows that this modification SD converges faster and efficient than the classical SD method.