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Solving the distributional worst-case in the distributionally robust optimization problem is equivalent to finding the projection onto the intersection of simplex and singly linear inequality constraint. This projection is a key component…

Optimization and Control · Mathematics 2025-02-18 Weimi Zhou , Yong-Jin Liu

We develop a globalized Proximal Newton method for composite and possibly non-convex minimization problems in Hilbert spaces. Additionally, we impose less restrictive assumptions on the composite objective functional considering…

Optimization and Control · Mathematics 2021-11-02 Bastian Pötzl , Anton Schiela , Patrick Jaap

A broad range of inverse problems can be abstracted into the problem of minimizing the sum of several convex functions in a Hilbert space. We propose a proximal decomposition algorithm for solving this problem with an arbitrary number of…

Optimization and Control · Mathematics 2009-11-13 Patrick L. Combettes , Jean-Christophe Pesquet

This paper is concerned with an algorithm for finding a singularity of the nonsmooth vector fields. Firstly, we discuss the main results of the Newton method presented in [1] for solving the aforementioned problem. Combining this method…

Optimization and Control · Mathematics 2020-06-03 Fabiana R. de Oliveira , Fabrícia R. Oliveira

A new equivalent reformulation of the absolute value equations associated with second-order cone (SOCAVEs) is emphasised, from which a dynamical system based on projection operator for solving SOCAVEs is constructed. Under proper…

Dynamical Systems · Mathematics 2022-08-11 Cairong Chen , Dongmei Yu , Deren Han , Changfeng Ma

We consider cylindrical algebraic decomposition (CAD) and the key concept of delineability which underpins CAD theory. We introduce the novel concept of projective delineability which is easier to guarantee computationally. We prove results…

Consider a polyhedral convex cone which is given by a finite number of linear inequalities. We investigate the problem to project this cone into a subspace and show that this problem is closely related to linear vector optimization: We…

Optimization and Control · Mathematics 2014-06-09 Andreas Löhne

A zero-finding technique for solving nonlinear equations more efficiently than they usually are with traditional iterative methods in which the order of convergence is improved is presented. The key idea in deriving this procedure is to…

Numerical Analysis · Mathematics 2011-06-07 Miquel Grau-Sánchez , José Luis Díaz-Barrero

Decomposition techniques for linear programming are difficult to extend to conic optimization problems with general non-polyhedral convex cones because the conic inequalities introduce an additional nonlinear coupling between the variables.…

Optimization and Control · Mathematics 2013-06-04 Yifan Sun , Martin S. Andersen , Lieven Vandenberghe

Fluid-solid interaction has been a challenging subject due to their strong nonlinearity and multidisciplinary nature. Many of the numerical methods for solving FSI problems have struggled with non-convergence and numerical instability. In…

Numerical Analysis · Mathematics 2018-02-07 Gangjoon Yoon , Chohong Min , Seick Kim

The Newton's method for solving stationary Navier-Stokes equations (NSE) is known to convergent fast, however, may fail due to a bad initial guess. This work presents a simple-to-implement nonlinear preconditioning of Newton's iteration,…

Numerical Analysis · Mathematics 2025-08-01 Muhammad Mohebujjaman , Mengying Xiao , Cheng Zhang

A type of iterative orthogonally accumulated projection methods for solving linear system of equations are proposed in this paper. This type of methods are applications of accumulated projection(AP) technique proposed recently by authors.…

Numerical Analysis · Mathematics 2016-08-24 Wujian Peng , Shuhua Zhang

In this paper we study the convergence of an iterative algorithm for finding zeros with constraints for not necessarily monotone set-valued operators in a reflexive Banach space. This algorithm, which we call the proximal-projection method…

Exactly Solvable and Integrable Systems · Physics 2007-11-16 Dan Butnariu , Gabor Kassay

When used to accelerate the convergence of fixed-point iterative methods, such as the Picard method, which is a kind of nonlinear fixed-point iteration, polynomial extrapolation techniques can be very effective. The numerical solution of…

Numerical Analysis · Mathematics 2025-01-07 Abdellatif Mouhssine , Ahmed Ratnani , Hassane Sadok

We present a partitioned Model Order Reduction method for multiphysics problems, that is based on a semi-implicit treatment of the coupling conditions, and on a projection scheme. The proposed Reduced Order Method is based on the Proper…

Numerical Analysis · Mathematics 2023-08-08 Monica Nonino , Francesco Ballarin , Gianluigi Rozza , Yvon Maday

We give a short survey on computational techniques which can be used to solve the representation conversion problem for polyhedra up to symmetries. We in particular discuss decomposition methods, which reduce the problem to a number of…

Metric Geometry · Mathematics 2011-10-20 David Bremner , Mathieu Dutour Sikiric , Achill Schuermann

We study the relation between sweeping processes with the cone of limiting normals and projection processes. We prove the existence of solution of a perturbed sweeping process with the cone of limiting normals and of nonstationary…

Optimization and Control · Mathematics 2017-11-10 Mira Bivas , Nadezhda Ribarska

The operator splitting approach applied to the Navier-Stokes equations, gave rise to various numerical methods for the simulations of the dynamics of fluids. The separate work of Chorin and Temam on this subject gave birth to the so-called…

Numerical Analysis · Mathematics 2019-07-24 J. Deteix , D. Yakoubi

This article is concerned with a geometric tool given by a pair of projector operators defined by almost product structures on finite dimensional manifolds, polarized by a distribution of constant rank and also endowed with some geometric…

Mathematical Physics · Physics 2011-10-11 Paulo Pitanga , Paulo R. Rodrigues

Composite minimization involves a collection of smooth functions which are aggregated in a nonsmooth manner. In the convex setting, we design an algorithm by linearizing each smooth component in accordance with its main curvature. The…

Optimization and Control · Mathematics 2019-03-26 Jérôme Bolte , Zheng Chen , Edouard Pauwels