W. W. Hager and H. Zhang, “A New Conjugate Gradient Method with Guaranteed Descent and an Efficient Line Search,” SIAM Journal on Optimization, Vol. 16, No. 1, 2005, pp. 170-192.

has been cited by the following article:

• TITLE: A Line Search Algorithm for Unconstrained Optimization

  AUTHORS: Gonglin Yuan, Sha Lu, Zengxin Wei

  KEYWORDS: Line Search, Unconstrained Optimization, Global Convergence, R-linear Convergence

  JOURNAL NAME: Journal of Software Engineering and Applications, Vol.3 No.5, May 24, 2010

  ABSTRACT: It is well known that the line search methods play a very important role for optimization problems. In this paper a new line search method is proposed for solving unconstrained optimization. Under weak conditions, this method possesses global convergence and R-linear convergence for nonconvex function and convex function, respectively. Moreover, the given search direction has sufficiently descent property and belongs to a trust region without carrying out any line search rule. Numerical results show that the new method is effective.