A New Spectral Conjugate Gradient Method and Its Global Convergence

Abstract

Combining the advantage of spectral-gradient method, a spectral conjugate gradient method for the global optimization is presented. This method has the property that the generated search direction is sufficiently descent without utilizing the line search. The proof of the convergence of the proposed method is given. Numerical experiments show that the method is efficient and feasible.