Title :
A sufficient descent hybrid conjugate gradient method and its global convergence for unconstrained optimization
Author :
Sun, Zhongbo ; Zhu, Tianxiao ; Gao, Haiyin
Author_Institution :
Dept. of Math. Educ., Northeast Normal Univ., Changchun, China
Abstract :
In this paper, a modified hybrid conjugate gradient method is proposed for solving unconstrained optimization problems and a new sufficient descent direction is proposed. The theoretical analysis shows that the algorithm is global convergence under some suitable conditions. Numerical results show that this algorithm is effective in unconstrained optimization problems.
Keywords :
conjugate gradient methods; convergence of numerical methods; optimisation; descent direction; global convergence; modified hybrid conjugate gradient method; numerical results; sufficient descent hybrid conjugate gradient method; unconstrained optimization; Algorithm design and analysis; Convergence; Convex functions; Educational institutions; Gradient methods; Sun; Hybrid conjugate gradient method; Sufficient descent direction; Unconstrained optimization problem;
Conference_Titel :
Control and Decision Conference (CCDC), 2012 24th Chinese
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4577-2073-4
DOI :
10.1109/CCDC.2012.6244111
