A New Family of Hybrid Conjugate Gradient Methods for Unconstrained Optimization
نویسندگان
چکیده
منابع مشابه
A new hybrid conjugate gradient algorithm for unconstrained optimization
In this paper, a new hybrid conjugate gradient algorithm is proposed for solving unconstrained optimization problems. This new method can generate sufficient descent directions unrelated to any line search. Moreover, the global convergence of the proposed method is proved under the Wolfe line search. Numerical experiments are also presented to show the efficiency of the proposed algorithm, espe...
متن کاملA family of hybrid conjugate gradient methods for unconstrained optimization
Conjugate gradient methods are an important class of methods for unconstrained optimization, especially for large-scale problems. Recently, they have been much studied. This paper proposes a three-parameter family of hybrid conjugate gradient methods. Two important features of the family are that (i) it can avoid the propensity of small steps, namely, if a small step is generated away from the ...
متن کاملA New Hybrid Conjugate Gradient Method Based on Eigenvalue Analysis for Unconstrained Optimization Problems
In this paper, two extended three-term conjugate gradient methods based on the Liu-Storey ({tt LS}) conjugate gradient method are presented to solve unconstrained optimization problems. A remarkable property of the proposed methods is that the search direction always satisfies the sufficient descent condition independent of line search method, based on eigenvalue analysis. The globa...
متن کاملNew hybrid conjugate gradient method for unconstrained optimization
Conjugate gradient methods are widely used for unconstrained optimization, especially large scale problems. Most of conjugate gradient methods don’t always generate a descent search direction, so the descent condition is usually assumed in the analyses and implementations. Dai and Yuan (1999) proposed the conjugate gradient method which generates a descent direction at every iteration. Yabe and...
متن کاملNew Hybrid Conjugate Gradient Algorithms for Unconstrained Optimization
New hybrid conjugate gradient algorithms are proposed and analyzed. In these hybrid algorithms the famous parameter k β is computed as a convex combination of the Polak-Ribière-Polyak and Dai-Yuan conjugate gradient algorithms. In one hybrid algorithm the parameter in convex combination is computed in such a way that the conjugacy condition is satisfied, independent of the line search. In the o...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Statistics, Optimization & Information Computing
سال: 2020
ISSN: 2310-5070,2311-004X
DOI: 10.19139/soic-2310-5070-480