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Uniformly regular equilibrium problems are natural generalizations of abstract equilibrium prob lems and they are defined over the uniformly prox-regular nonconvex sets. Some new efficient implicit methods for solving uniformly regular…

Optimization and Control · Mathematics 2025-02-11 Oday Hazaimah

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 study mixed-integer programming (MIP) relaxation techniques for the solution of non convex mixed-integer quadratically constrained quadratic programs (MIQCQPs). We present MIP relaxation methods for non convex continuous variable…

Optimization and Control · Mathematics 2023-08-21 Benjamin Beach , Robert Burlacu , Andreas Bärmann , Lukas Hager , Robert Hildebrand

Randomized compilation protocols have recently attracted attention as alternatives to traditional deterministic Trotter-Suzuki methods, potentially reducing circuit depth and resource overhead. These protocols determine gate application…

Quantum Physics · Physics 2025-12-22 Yun-Zhuo Fan , Yu-Xia Wu , Dan-Bo Zhang

In this paper, we propose and study the iteration complexity of an inexact Douglas-Rachford splitting (DRS) method and a Douglas-Rachford-Tseng's forward-backward (F-B) splitting method for solving two-operator and four-operator monotone…

Optimization and Control · Mathematics 2017-12-01 M. Marques Alves , M. Geremia

Two new approaches to solving first-order quasilinear elliptic systems of PDEs in many dimensions are proposed. The first method is based on an analysis of multimode solutions expressible in terms of Riemann invariants, based on links…

Mathematical Physics · Physics 2014-10-01 A. M. Grundland , V. Lamothe

Current state-of-the-art solvers for mixed-integer programming (MIP) problems are designed to perform well on a wide range of problems. However, for many real-world use cases, problem instances come from a narrow distribution. This has…

Optimization and Control · Mathematics 2022-02-15 Charly Robinson La Rocca , Emma Frejinger , Jean-François Cordeau

Planning in hybrid systems with both discrete and continuous control variables is important for dealing with real-world applications such as extra-planetary exploration and multi-vehicle transportation systems. Meanwhile, generating…

Robotics · Computer Science 2021-02-23 Jingkai Chen , Brian Williams , Chuchu Fan

This paper introduces the multiplicative variant of the recently proposed asynchronous additive coarse-space correction method. Definition of an asynchronous extension of multiplicative correction is not straightforward, however, our…

Numerical Analysis · Mathematics 2023-12-20 Guillaume Gbikpi-Benissan , Frédéric Magoulès

Covering and elimination inequalities are central to combinatorial optimization, yet their role has largely been studied in problem-specific settings or via no-good cuts. This paper introduces a unified perspective that treats these…

Optimization and Control · Mathematics 2025-11-18 Ningji Wei

The paper proposes a novel hybrid method for solving equilibrium problems and fixed point problems. By constructing specially cutting-halfspaces, in this algorithm, only an optimization program is solved at each iteration without the…

Optimization and Control · Mathematics 2015-10-30 Dang Van Hieu

Large-scale strongly nonlinear and nonconvex mixed-integer nonlinear programming (MINLP) models frequently appear in optimisation-based process synthesis, integration, intensification, and process control. However, they are usually…

Optimization and Control · Mathematics 2026-01-06 Yingjie Ma , Jie Li

This paper is an attempt to solve an important class of hypersingular integral equations of the second kind. To this end, we apply a new weighted and modified perturbation method which includes some special cases of the Adomian…

Classical Analysis and ODEs · Mathematics 2017-06-08 Mostafa Akrami , Taher Lotfi , Farajollah Mohammadi Yaghoobi

This paper describes and establishes the iteration-complexity of a doubly accelerated inexact proximal point (D-AIPP) method for solving the nonconvex composite minimization problem whose objective function is of the form $f+h$ where $f$ is…

Optimization and Control · Mathematics 2018-12-20 Jiaming Liang , Renato D. C. Monteiro

The relaxation complexity rc(X) of the set of integer points X contained in a polyhedron is the minimal number of inequalities needed to formulate a linear optimization problem over X without using auxiliary variables. Besides its relevance…

Optimization and Control · Mathematics 2022-03-14 Gennadiy Averkov , Christopher Hojny , Matthias Schymura

A new class of implicit-explicit (IMEX) methods combined with a p-adaptive mixed finite element formulation is proposed to simulate the diffusion of reacting species. Hierarchical polynomial functions are used to construct an…

The aim of this paper is to investigate the use of an entropic projection method for the iterative regularization of linear ill-posed problems. We derive a closed form solution for the iterates and analyze their convergence behaviour both…

Optimization and Control · Mathematics 2020-01-29 Martin Burger , Elena Resmerita , Martin Benning

Optimization-based solvers play a central role in a wide range of signal processing and communication tasks. However, their applicability in latency-sensitive systems is limited by the sequential nature of iterative methods and the high…

Signal Processing · Electrical Eng. & Systems 2026-03-12 Dvir Avrahami , Amit Milstein , Caroline Chaux , Tirza Routtenberg , Nir Shlezinger

This paper investigates a Halpern acceleration of the inexact proximal point method for solving maximal monotone inclusion problems in Hilbert spaces. The proposed Halpern inexact proximal point method (HiPPM) is shown to be globally…

Optimization and Control · Mathematics 2026-01-08 Liwei Zhang , Fanli Zhuang , Ning Zhang

For complex, high-dimensional Markov Decision Processes (MDPs), it may be necessary to represent the policy with function approximation. A problem is misspecified whenever, the representation cannot express any policy with acceptable…

Machine Learning · Computer Science 2016-06-09 Daniel J. Mankowitz , Timothy A. Mann , Shie Mannor
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