[图书][B] The theory and applications of iteration methods

IK Argyros - 2022 - taylorfrancis.com
The theory and applications of Iteration Methods is a very fast-developing field of numerical
analysis and computer methods. The second edition is completely updated and continues to …

A modified conjugate gradient method for monotone nonlinear equations with convex constraints

AM Awwal, P Kumam, AB Abubakar - Applied Numerical Mathematics, 2019 - Elsevier
In this paper, a modified Hestenes-Stiefel (HS) spectral conjugate gradient (CG) method for
monotone nonlinear equations with convex constraints is proposed based on projection …

A locally convergent inexact projected Levenberg–Marquardt-type algorithm for large-scale constrained nonsmooth equations

FR de Oliveira, FR de Oliveira - Journal of Computational and Applied …, 2023 - Elsevier
This work presents a variant of an inexact projected Levenberg–Marquardt algorithm for
solving constrained nonsmooth equations. More precisely, we propose a local inexact …

A new conjugate gradient projection method for convex constrained nonlinear equations

P Liu, J Jian, X Jiang - Complexity, 2020 - Wiley Online Library
The conjugate gradient projection method is one of the most effective methods for solving
large‐scale monotone nonlinear equations with convex constraints. In this paper, a new …

Newton's method with feasible inexact projections for solving constrained generalized equations

FR de Oliveira, OP Ferreira, GN Silva - Computational Optimization and …, 2019 - Springer
This paper aims to address a new version of Newton's method for solving constrained
generalized equations. This method can be seen as a combination of the classical Newton's …

Exploiting problem structure in derivative free optimization

M Porcelli, PL Toint - ACM Transactions on Mathematical Software …, 2022 - dl.acm.org
A structured version of derivative-free random pattern search optimization algorithms is
introduced, which is able to exploit coordinate partially separable structure (typically …

An inexact projected LM type algorithm for solving convex constrained nonlinear equations

DS Gonçalves, MLN Gonçalves, FR Oliveira - Journal of Computational …, 2021 - Elsevier
In this paper, we propose two complementary variants of the projected Levenberg–
Marquardt (LM) algorithm for solving convex constrained nonlinear equations. Since the …

Greedy and random Broyden's methods with explicit superlinear convergence rates in nonlinear equations

H Ye, D Lin, Z Zhang - arXiv preprint arXiv:2110.08572, 2021 - arxiv.org
In this paper, we propose the greedy and random Broyden's method for solving nonlinear
equations. Specifically, the greedy method greedily selects the direction to maximize a …

An inexact Newton-like conditional gradient method for constrained nonlinear systems

MLN Gonçalves, FR Oliveira - Applied Numerical Mathematics, 2018 - Elsevier
In this paper, we propose an inexact Newton-like conditional gradient method for solving
constrained systems of nonlinear equations. The local convergence of the new method as …

Newton's method for solving generalized equations without Lipschitz condition

J Wang, W Ouyang - Journal of Optimization Theory and Applications, 2022 - Springer
This paper aims to establish higher order convergence of the (inexact) Newton's method for
solving generalized equations composed of the sum of a single-valued mapping and a set …