A new family of Polak-Ribiere-Polyak conjugate gradient method with the strong-Wolfe line search

2017 ◽  
Author(s):  
Nur Hamizah Abdul Ghani ◽  
Mustafa Mamat ◽  
Mohd Rivaie
Keyword(s):  
Conjugate Gradient Method ◽  
Conjugate Gradient ◽  
Gradient Method ◽  
Line Search ◽  
New Family ◽  
Strong Wolfe Line Search ◽  
Wolfe Line Search

Two-Parameter Conjugate Gradient Projection Method and its Application

2014 ◽  
Vol 989-994 ◽  
pp. 1802-1805
Author(s):  
Hong Fang Cui
Keyword(s):  
Conjugate Gradient Method ◽  
Projection Method ◽  
Conjugate Gradient ◽  
Gradient Method ◽  
Line Search ◽  
Linear Constraints ◽  
Convergence Criteria ◽  
Strong Wolfe Line Search ◽  
Wolfe Line Search ◽  
Two Parameter

On the basis of the conjugate gradient method CD, the artile builds a new two-parameter P-NCD projected conjugate gradient method, the article gives two-parameter P-NCD Conjugate Gradient Method drop projection and on the strong Wolfe line search in the principles of the convergence criteria, the new algorithm is applied to estimate the equation with linear constraints in the model instantiated test ,the results shows good results.

scholarly journals A modified quadratic hybridization of Polak-Ribiere-Polyak and Fletcher-Reeves conjugate gradient method for unconstrained optimization problems

2017 ◽  
Vol 7 (2) ◽  
pp. 177-185 ◽  
Author(s):  
Pro Kaelo ◽  
Sindhu Narayanan ◽  
M.V. Thuto
Keyword(s):  
Unconstrained Optimization ◽  
Conjugate Gradient Method ◽  
Conjugate Gradient ◽  
Gradient Method ◽  
Line Search ◽  
Optimization Problems ◽  
Unconstrained Optimization Problems ◽  
Strong Wolfe Line Search ◽  
Wolfe Line Search ◽  
Hybrid Conjugate Gradient Method

This article presents a modified quadratic hybridization of the Polak–Ribiere–Polyak and Fletcher–Reeves conjugate gradient method for solving unconstrained optimization problems. Global convergence, with the strong Wolfe line search conditions, of the proposed quadratic hybrid conjugate gradient method is established. We also report some numerical results to show the competitiveness of the new hybrid method.

A new hybrid conjugate gradient method of unconstrained optimization methods

2021 ◽  
pp. 2250070
Author(s):  
Chenna Nasreddine ◽  
Sellami Badreddine ◽  
Belloufi Mohammed
Keyword(s):  
Unconstrained Optimization ◽  
Conjugate Gradient Method ◽  
Conjugate Gradient ◽  
Gradient Method ◽  
Line Search ◽  
Convex Combination ◽  
Optimization Methods ◽  
Strong Wolfe Line Search ◽  
Wolfe Line Search ◽  
Hybrid Conjugate Gradient Method

In this paper, we present a new hybrid method to solve a nonlinear unconstrained optimization problem by using conjugate gradient, which is a convex combination of Liu–Storey (LS) conjugate gradient method and Hager–Zhang (HZ) conjugate gradient method. This method possesses the sufficient descent property with Strong Wolfe line search and the global convergence with the strong Wolfe line search. In the end of this paper, we illustrate our method by giving some numerical examples.

scholarly journals A globally convergent hybrid conjugate gradient method with strong Wolfe conditions for unconstrained optimization

2019 ◽  
Vol 14 (1) ◽  
pp. 1-9
Author(s):  
P. Kaelo ◽  
P. Mtagulwa ◽  
M. V. Thuto
Keyword(s):  
Conjugate Gradient Method ◽  
Conjugate Gradient ◽  
Gradient Method ◽  
Line Search ◽  
Gradient Methods ◽  
Convergence Properties ◽  
Good Convergence ◽  
Strong Wolfe Line Search ◽  
Wolfe Line Search ◽  
Hybrid Conjugate Gradient Method

Abstract In this paper, we develop a new hybrid conjugate gradient method that inherits the features of the Liu and Storey (LS), Hestenes and Stiefel (HS), Dai and Yuan (DY) and Conjugate Descent (CD) conjugate gradient methods. The new method generates a descent direction independently of any line search and possesses good convergence properties under the strong Wolfe line search conditions. Numerical results show that the proposed method is robust and efficient.

scholarly journals A new hybrid conjugate gradient method for dynamic force reconstruction

2019 ◽  
Vol 11 (1) ◽  
pp. 168781401882236
Author(s):  
Linjun Wang ◽  
Liu Xu ◽  
Youxiang Xie ◽  
Yixian Du ◽  
Xiao Han
Keyword(s):  
Conjugate Gradient Method ◽  
Conjugate Gradient ◽  
Gradient Method ◽  
Present Method ◽  
Line Search ◽  
Dynamic Force ◽  
Load Identification ◽  
Strong Wolfe Line Search ◽  
Wolfe Line Search ◽  
Hybrid Conjugate Gradient Method

A new hybrid conjugate gradient method is proposed in this article based on the gradient operator and applied to the structural dynamic load identification problem. It has proved that the present method with the strong Wolfe line search possesses sufficient descent property. In addition, the present method is globally convergent when the parameter in the strong Wolfe line search conditions is restricted in some suitable intervals. Three example problems from engineering are solved by the newly developed conjugate gradient method to demonstrate the robustness and effectiveness of conjugate gradient method in solving multi-source dynamic load identification problems. Compared with the traditional Landweber iteration regularization method (Landweber), the proposed conjugate gradient method can more stably and effectively overcome the influences of noise, largely reduce the number of iterations, and provide accurate results in identifying multi-source dynamic force in practical engineering structure.

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