G. Yuan, X. Lu, and Z. Wei, “A Conjugate Gradient Method with Descent Direction for Unconstrained Optimi- zation,” Journal of Computational and Applied Mathe- matics, Vol. 233, No. 2, 2009, pp. 519-530.

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.