Effect Conjugate Gradient Method for Solving Nonlinear Optimization Problems

Conjugate gradient techniques are widely used to solve unconstrained optimization issues. The accelerated conjugate gradient approach provides superior numerical effects for the unconstrained optimization problems as compared to the conjugate gradient method. In this work, we provide a modified conjugate gradient approach that produces the direction of descent via Wolfe line search. We demonstrate that the suggested approach is globally convergent under moderate circumstances. The suggested approach is significant for our test functions, according to numerical data.