A new spectral three term conjugate gradient method with random parameter is proposed. by minimizing the frobenius norm distance between search direction q k 1 and ml bfgs matrix based on the modified secant equation, the parameter t k in q k 1 is determined, and the random parameter is introduced to simplify the scheme of t k. the search. In this paper, we proposed a new spectral conjugate gradient method by [18]. table 1 shows the standard test problems used in this article. table 1: list of standard test problems.
Spectral conjugate gradient (scg) methods are combinations of spectral gradient method and conjugate gradient (cg) methods, which have been well studied in euclidean space. in this paper, we aim to extend this class of methods to solve optimization problems on riemannian manifolds. firstly, we present a riemannian version of the spectral parameter, which guarantees that the search direction. In this paper, according to some suitable features of three term conjugate gradient methods and excellent theoretical properties of the quasi newton methods, a new spectral three term conjugate gradient is proposed. a modified secant condition is used to compute a suitable spectral parameter. the new search direction ensures the sufficient descent condition without any line search. it is. 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 convergence result and thus, imposed certain restricted rmil cg parameter as a remedy. in this paper, we suggest an efficient rmil spectral cg method. the remarkable feature of this method is that, the convergence. The spectral conjugate gradient (scg) method is an effective method to solve large scale nonlinear unconstrained optimization problems. in this work, we propose a new scg method in which.
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 convergence result and thus, imposed certain restricted rmil cg parameter as a remedy. in this paper, we suggest an efficient rmil spectral cg method. the remarkable feature of this method is that, the convergence. The spectral conjugate gradient (scg) method is an effective method to solve large scale nonlinear unconstrained optimization problems. in this work, we propose a new scg method in which. One of the most important spectral conjugate gradient methods is proposed by bergin and martínez in [8]. in this method, the conjugate parameter β k is defined as (1.4) β k = (θ k − 1 y k − 1 − s k − 1) t g k d k − 1 t y k − 1, where s k − 1 = x k − x k − 1, y k − 1 = g k − g k − 1. if θ k ≡ 1 holds, it reduces to. Spectral conjugate gradient method (scgm) is an important generalization of the conjugate gradient method (cgm), and it is also one of the effective numerical methods for large scale unconstrained optimization. the designing for the spectral parameter and the conjugate parameter in scgm is a core work. and the aim of this paper is to propose a new and effective alternative method for these two.
One of the most important spectral conjugate gradient methods is proposed by bergin and martínez in [8]. in this method, the conjugate parameter β k is defined as (1.4) β k = (θ k − 1 y k − 1 − s k − 1) t g k d k − 1 t y k − 1, where s k − 1 = x k − x k − 1, y k − 1 = g k − g k − 1. if θ k ≡ 1 holds, it reduces to. Spectral conjugate gradient method (scgm) is an important generalization of the conjugate gradient method (cgm), and it is also one of the effective numerical methods for large scale unconstrained optimization. the designing for the spectral parameter and the conjugate parameter in scgm is a core work. and the aim of this paper is to propose a new and effective alternative method for these two.
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