Performance of New Line Search Methods with Three-Term Hybrid Descent Approach for Unconstrained Optimization Problems

In this paper, l demonstrates the performance and efficiency of new line search methods with three-term hybrid descent method for the solution of unconstrained optimization problems (UOPs). The techniques advanced the sustainable range of step-length to a broader level than the previous studies and gave a suitable initial step-length at each step of the iterations. The global convergence rate of the new line with three-term hybrid descent method search is carried studied. Some numerical results through performance profile shows that among the new search method modified Wolfe line search method in CPU time and iterations is best in practical computation.