A new simple conjugate gradient coefficient for unconstrained optimization

Conjugate gradient method holds an important role in solving unconstrained optimizations, especially for large scale problems. Numerous studies and modifications have been done to improve this method. In this paper, we propose a fundamentally different conjugate gradient method in which the well known coefficient β k is computed using the eigenvalues generated by using exact Hessian matrix of f ( x ) . This relatively easy formula for β k has...