In this paper we study parameterization as a tool for both constructing and smoothing spatial triangulations. Most of the parameterization methods we study are based on convex combination maps, which have the property that the image of each interior vertex is a convex combination of its neighbours. When mapping an existing triangulation, this latter property ensures that whenever the image of t...

Conjugate gradient methods are among the most efficient for solving optimization models. In this paper, a newly proposed conjugate method is problems as convex combination of Harger-Zhan and Dai-Yaun nonlinear methods, which capable producing sufficient descent condition with global convergence properties under strong Wolfe conditions. The numerical results demonstrate efficiency some benchmark...