The global convergence of spectral RMIL conjugate gradient method for unconstrained optimization with applications to robotic model and image recovery
In 2012, Rivaie et al. introduced RMIL conjugate gradient (CG) method which is globally
convergent under the exact line search. Later, Dai (2016) pointed out abnormality in the …
convergent under the exact line search. Later, Dai (2016) pointed out abnormality in the …
A family of hybrid conjugate gradient method with restart procedure for unconstrained optimizations and image restorations
X Jiang, X Ye, Z Huang, M Liu - Computers & Operations Research, 2023 - Elsevier
Conjugate gradient method is one of the most effective methods for solving large-scale
optimization problems. Based on the CD conjugate parameter and an improved PRP …
optimization problems. Based on the CD conjugate parameter and an improved PRP …
An efficient Newton-like conjugate gradient method with restart strategy and its application
In an attempt to enhance the theoretical structure of the Hestenes and Stiefel (HS) conjugate
gradient method, several modifications of the method are provided, most of which rely on a …
gradient method, several modifications of the method are provided, most of which rely on a …
A revised Liu–Storey conjugate gradient parameter for unconstrained optimization problems with applications
Conjugate Gradient (CG) methods are renowned for their efficiency and low memory
requirements when solving optimization problems. However, certain formulations of CG …
requirements when solving optimization problems. However, certain formulations of CG …
Modified spectral conjugate gradient iterative scheme for unconstrained optimization problems with application on COVID-19 model
In this work, a new class of spectral conjugate gradient (CG) method is proposed for solving
unconstrained optimization models. The search direction of the new method uses the ZPRP …
unconstrained optimization models. The search direction of the new method uses the ZPRP …
A Family of Developed Hybrid Four-Term Conjugate Gradient Algorithms for Unconstrained Optimization with Applications in Image Restoration
E Ali, S Mahdi - Symmetry, 2023 - mdpi.com
The most important advantage of conjugate gradient methods (CGs) is that these methods
have low memory requirements and convergence speed. This paper contains two main …
have low memory requirements and convergence speed. This paper contains two main …
Some combined techniques of spectral conjugate gradient methods with applications to robotic and image restoration models
The spectral conjugate gradient (SCG) methods ensure the descent property of an iterative
scheme by scaling the first term of the search direction in a conjugate gradient (CG) method …
scheme by scaling the first term of the search direction in a conjugate gradient (CG) method …
A Modified Wei-Yao-Liu Conjugate Gradient Method for Unconstrained Optimization and Motion Control of Robotic Motion Manipulators
SN Alsuliman, NF Ibrahim… - Journal of Advanced …, 2024 - semarakilmu.com.my
The WYL-type conjugate gradient (CG) iterative formulas have been widely studied by
researchers because of their effective and robust algorithms as well as less memory …
researchers because of their effective and robust algorithms as well as less memory …
New CG-Based Algorithms with Second-Order Curvature Information for NLS Problems and a 4DOF Arm Robot Model
This article develops two new algorithms of three-term conjugate gradient (TTCG)
coefficients to handle nonlinear least-squares (NLS) problems using the structured secant …
coefficients to handle nonlinear least-squares (NLS) problems using the structured secant …
A sufficient descent hybrid conjugate gradient method without line search consideration and application
Purpose Previous RMIL versions of the conjugate gradient method proposed in literature
exhibit sufficient descent with Wolfe line search conditions, yet their global convergence …
exhibit sufficient descent with Wolfe line search conditions, yet their global convergence …