Yu, G.H. (2007) Nonlinear self-scaling conjugate gradient methods for large-scale optimization problems. Thesis of Doctor’s Degree, Sun Yat-Sen University.

has been cited by the following article:

• TITLE: A hybrid conjugate gradient method for optimization problems

  AUTHORS: Xiangrong Li, Xupei Zhao

  KEYWORDS: Line Search; Unconstrained Optimization; Conjugate Gradient Method; Global Convergence

  JOURNAL NAME: Natural Science, Vol.3 No.1, January 29, 2011

  ABSTRACT: A hybrid method of the Polak-Ribière-Polyak (PRP) method and the Wei-Yao-Liu (WYL) method is proposed for unconstrained optimization pro- blems, which possesses the following properties: i) This method inherits an important property of the well known PRP method: the tendency to turn towards the steepest descent direction if a small step is generated away from the solution, preventing a sequence of tiny steps from happening; ii) The scalar holds automatically; iii) The global convergence with some line search rule is established for nonconvex functions. Numerical results show that the method is effective for the test problems.