Title :
Convergence property of a class of unconstrained minimization methods with perturbations
Author :
Li, Meixia ; Che, Haitao
Author_Institution :
Sch. of Math. & Inf. Sci., Weifang Univ., Weifang, China
Abstract :
In this paper, we investigate a class of unconstrained minimization methods including Fletcher-Reeves (abbr. FR) conjugate gradient method with perturbations. Their stepsizes are determined by generalized Wolfe line search. We prove that these methods are globally convergent under mild conditions, and in doing so, we remove various boundedness conditions such as boundedness from blow of f, boundedness of level set, etc. At the end of this paper, numerical examples are given.
Keywords :
conjugate gradient methods; convergence; minimisation; Fletcher-Reeves conjugate gradient method; convergence property; generalized Wolfe line search; perturbations; unconstrained minimization methods; Algorithm design and analysis; Communication system control; Convergence; Gradient methods; Information science; Level set; Mathematics; Minimization methods; Neural networks; Optimization methods; global convergence; perturbation; unconstrained optimization method;
Conference_Titel :
Computing, Communication, Control, and Management, 2009. CCCM 2009. ISECS International Colloquium on
Conference_Location :
Sanya
Print_ISBN :
978-1-4244-4247-8
DOI :
10.1109/CCCM.2009.5267980
