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Optimization problems in engineering and applied mathematics are typically solved in an iterative fashion, by systematically adjusting the variables of interest until an adequate solution is found. The iterative algorithms that govern these…

Optimization and Control · Mathematics 2022-05-31 Laurent Lessard

Implied-integer detection is a well-known presolving technique that is used by many Mixed-Integer Linear Programming solvers. Informally, a variable is said to be implied integer if its integrality is enforced implicitly by integrality of…

Discrete Mathematics · Computer Science 2025-07-15 Rolf van der Hulst , Matthias Walter

We recall the concept of Baxterisation of an R-matrix, or of a monodromy matrix, which corresponds to build, from one point in the $ R$-matrix parameter space, the algebraic variety where the spectral parameter(s) live. We show that the…

High Energy Physics - Theory · Physics 2015-06-25 S. Boukraa , J-M. Maillard

Inverse optimization describes a process that is the "reverse" of traditional mathematical optimization. Unlike traditional optimization, which seeks to compute optimal decisions given an objective and constraints, inverse optimization…

Optimization and Control · Mathematics 2022-07-28 Timothy C. Y. Chan , Rafid Mahmood , Ian Yihang Zhu

Quantum optimization algorithms hold the promise of solving classically hard, discrete optimization problems in practice. The requirement of encoding such problems in a Hamiltonian realized with a finite -- and currently small -- number of…

Quantum Physics · Physics 2023-07-10 Yifeng Rocky Zhu , David Joseph , Cong Ling , Florian Mintert

We introduce an efficient way, called Newton algorithm, to study arbitrary ideals in C[[x,y]], using a finite succession of Newton polygons. We codify most of the data of the algorithm in a useful combinatorial object, the Newton tree. For…

Algebraic Geometry · Mathematics 2014-02-26 Pierrette Cassou-Noguès , Willem Veys

An efficient direct solver for volume integral equations with O(N) complexity for a broad range of problems is presented. The solver relies on hierarchical compression of the discretized integral operator, and exploits that off-diagonal…

Numerical Analysis · Mathematics 2013-05-16 Eduardo Corona , Per-Gunnar Martinsson , Denis Zorin

The Riccati equations reducible to first-order linear equations by an appropriate change the dependent variable are singled out. All these equations are integrable by quadrature. A wide class of linear ordinary differential equations…

Classical Analysis and ODEs · Mathematics 2011-08-02 Nail H. Ibragimov

This study aims to discuss the existence and uniqueness of solution of fuzzy Volterra integral equation with piecewise continuous kernel. Such problems appears in many balance problems for hereditary dynamic systems, e.g. in electric load…

General Mathematics · Mathematics 2024-01-18 Samad Noeiaghdam , Aliona I. Dreglea , Denis N. Sidorov

An algorithm is given for computing explicit formulas for the generators of relations among the invariant rational functions for vector-valued bilinear forms. These formulas have applications in the geometry of Riemannian submanifolds and…

Rings and Algebras · Mathematics 2007-05-23 Thomas Garrity , Zachary Grossman

Sharp upper and lower estimates are obtained of the approximation numbers of a Sobolev embedding and an integral operator of Volterra type. These lead to asymptotic formulae for the approximation numbers and certain other s-numbers.

Functional Analysis · Mathematics 2015-04-13 David E. Edmunds , Jan Lang

This paper deals with inverse problems subject to imprecise or vague information of some involved data by means of interval-valued functions. To provide interval solutions to the inverse problems we have adopted a perturbed collage-based…

Numerical Analysis · Mathematics 2020-07-15 M. Arana-Jimenez , M. I. Berenguer , D. Gamez , A. I Garralda-Guillem , M. Ruiz Galan

We discuss the application of multistep collocation methods to Volterra integral equations which contain a weakly singular kernel $(t-\tau)^{\alpha-1}$ with $0 <\alpha <1.$ Convergence orders of the methods are determined and their…

Numerical Analysis · Mathematics 2014-12-17 D. Nazari Susahab , S. Shahmorad

This paper considers a numeric algorithm to solve the equation \begin{align*} y(t)=f(t)+\int^t_0 g(t-\tau)y(\tau)\,d\tau \end{align*} with a kernel $g$ and input $f$ for $y$. In some applications we have a smooth integrable kernel but the…

Numerical Analysis · Mathematics 2019-08-09 Leanne Dong , John van der Hoek

The problem of numerical differentiation can be thought of as an inverse problem by considering it as solving a Volterra equation. It is well known that such inverse integral problems are ill-posed and one requires regularization methods to…

Numerical Analysis · Mathematics 2020-04-15 Abinash Nayak

In most introductory numerical analysis textbooks, the treatment of a single nonlinear equation often consists of a collection of all-purpose methods that frequently do not work or are inefficient. These textbooks neglect to teach the…

Numerical Analysis · Mathematics 2022-04-06 Aaron Melman

Integral transformations are used to estimate high order derivatives of various special functions. Applications are given to numerical integration, where estimates of high order derivatives of the integrand are needed to achieve bounds on…

Numerical Analysis · Mathematics 2007-06-21 David M. Bradley

We introduce an iterated integral version of (generalized) log-sine integrals (iterated log-sine integrals) and prove a relation between a multiple polylogarithm and iterated log-sine integrals. We also give a new method for obtaining…

Number Theory · Mathematics 2019-04-23 Ryota Umezawa

This paper presents a high-order accurate numerical quadrature algorithm for evaluating integrals over curved surfaces and regions defined implicitly via a level set of a given function restricted to a hyperrectangle. The domain is divided…

Numerical Analysis · Mathematics 2025-06-17 Zibo Zhao

An algorithm is proposed, analyzed, and tested experimentally for solving stochastic optimization problems in which the decision variables are constrained to satisfy equations defined by deterministic, smooth, and nonlinear functions. It is…

Optimization and Control · Mathematics 2021-07-09 Frank E. Curtis , Daniel P. Robinson , Baoyu Zhou
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