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The focus in this paper is interior-point methods for bound-constrained nonlinear optimization, where the system of nonlinear equations that arise are solved with Newton's method. There is a trade-off between solving Newton systems…

Optimization and Control · Mathematics 2023-05-04 David Ek , Anders Forsgren

In this work, we introduce an iterative linearised finite element method for the solution of Bingham fluid flow problems. The proposed algorithm has the favourable property that a subsequence of the sequence of iterates generated converges…

Numerical Analysis · Mathematics 2021-09-14 Pascal Heid , Endre Süli

The finite element method is a well-established method for the numerical solution of partial differential equations (PDEs), both linear and nonlinear. However, the repeated reassemblage of finite element matrices for nonlinear PDEs is…

Numerical Analysis · Mathematics 2022-09-12 Yannis Voet

Many combinatorial optimisation problems can be modelled as valued constraint satisfaction problems. In this paper, we present a polynomial-time algorithm solving the valued constraint satisfaction problem for a fixed number of variables…

Optimization and Control · Mathematics 2020-03-03 Manuel Bodirsky , Marcello Mamino , Caterina Viola

We propose an iterative method for nonlinear semidefinite programs with box constraints. The search direction in the proposed method utilizes the distance from the current point to the boundary of a feasible set. The computation of the…

Optimization and Control · Mathematics 2015-05-15 Akihiko Komatsu , Makoto Yamashita

Newton method is one of the most powerful methods for finding solutions of nonlinear equations and for proving their existence. In its "pure" form it has fast convergence near the solution, but small convergence domain. On the other hand…

Optimization and Control · Mathematics 2019-08-27 Boris Polyak , Andrey Tremba

In this paper, we propose new proximal Newton-type methods for convex optimization problems in composite form. The applications include model predictive control (MPC) and embedded MPC. Our new methods are computationally attractive since…

Optimization and Control · Mathematics 2020-07-21 Ilan Adler , Zhiyue Tom Hu , Tianyi Lin

In this paper is described the general aspect of a numerical method for piecewise determin-istic Markov processes with boundary. Under very natural hypotheses, a crucial result about uniqueness of solution of a generalized Kolmogorov…

Analysis of PDEs · Mathematics 2018-10-25 Ludovic Goudenège

We distinguish two kinds of piecewise linear functions and provide an interesting representation for a piecewise linear function between two normed spaces. Based on such a representation, we study a fully piecewise linear vector…

Optimization and Control · Mathematics 2020-09-23 Xiyin Zheng , Xiaoqi Yang

We are concerned with the tensor equations whose coefficient tensor is an M-tensor. We first propose a Newton method for solving the equation with a positive constant term and establish its global and quadratic convergence. Then we extend…

Optimization and Control · Mathematics 2021-01-28 Dong-Hui Li Jie-Feng Xu , Hong-Bo Guan

This paper presents a general convergence theory of penalty based numerical methods for elliptic constrained inequality problems, including variational inequalities, hemivariational inequalities, and variational-hemivariational…

Numerical Analysis · Mathematics 2019-12-18 Weimin Han , Mircea Sofonea

When studying the multilinear PageRank problem, a system of polynomial equations needs to be solved. In this paper, we develop convergence theory for a modified Newton method in a particular parameter regime. The sequence of vectors…

Numerical Analysis · Mathematics 2017-01-23 Pei-Chang Guo

In this paper, we derive a practical, general framework for creating adaptive iterative (linearization or splitting) algorithms to solve multi-physics problems. This means that, given an iterative method, we derive \textit{a posteriori}…

Numerical Analysis · Mathematics 2026-01-26 Jakob S. Stokke , Kundan Kumar , Florin A. Radu

In this work we introduce and analyze a new multiscale method for strongly nonlinear monotone equations in the spirit of the Localized Orthogonal Decomposition. A problem-adapted multiscale space is constructed by solving linear local…

Numerical Analysis · Mathematics 2020-12-16 Barbara Verfürth

We extend the use of piecewise orthogonal collocation to computing periodic solutions of renewal equations, which are particularly important in modeling population dynamics. We prove convergence through a rigorous error analysis. Finally,…

Numerical Analysis · Mathematics 2023-12-08 Alessia Ando' , Dimitri Breda

A three-point iterative method for solving scalar non-linear equations was selected and then adapted to solve systems of non-linear equations. Subsequently, by applying Taylor's theorem to functions of $\R^{n}$ in $\R^{n}$, it is shown that…

General Mathematics · Mathematics 2026-01-23 Carlos E. Cadenas R. , Yorman J. Mendoza N

The nonlinear eigen-problem $ Ax+F(x)=\lambda x$ is studied where $A$ is an $n\times n$ irreducible Stieltjes matrix. Under certain conditions, this problem has a unique positive solution. We show that, starting from a multiple of the…

Numerical Analysis · Mathematics 2022-01-11 Peichang Guo

We study a class of monotone inclusions called "self-concordant inclusion" which covers three fundamental convex optimization formulations as special cases. We develop a new generalized Newton-type framework to solve this inclusion. Our…

Optimization and Control · Mathematics 2017-07-25 Quoc Tran-Dinh , Tianxiao Sun , Shu Lu

We clarify how close a second order fully nonlinear equation can come to uniform ellipticity, through counting large eigenvalues of the linearized operator. This suggests an effective and novel way to understand the structure of fully…

Differential Geometry · Mathematics 2022-10-12 Rirong Yuan

Finite elasticity problems commonly include material and geometric nonlinearities and are solved using various numerical methods. However, for highly nonlinear problems, achieving convergence is relatively difficult and requires small load…

Numerical Analysis · Mathematics 2018-05-01 Yue Mei , Daniel E. Hurtado , Sanjay Pant , Ankush Aggarwal
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