A New Scaled Three-Term Conjugate Gradient Algorithms For Unconstrained Optimization

Abstract

Since optimization problems are getting more complicated, new ways to solve them must be thought of, or existing methods must be improved. In this research, we expand the different parameters of the three-term conjugate gradient method to work out unconstrained optimization problems. Our new CG approach meets the conditions of sufficient descent, and global convergence. In addition, we describe some numerical results that imply comparisons to relevant methodologies in the existing research literature.