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We show that maximal $S$-free convex sets are polyhedra when $S$ is the set of integral points in some rational polyhedron of $\mathbb{R}^n$. This result extends a theorem of Lov\'asz characterizing maximal lattice-free convex sets. Our…

Optimization and Control · Mathematics 2017-01-24 Amitabh Basu , Michele Conforti , Gerard Cornuejols , Giacomo Zambelli

A convex set with nonempty interior is maximal lattice-free if it is inclusion-maximal with respect to the property of not containing integer points in its interior. Maximal lattice-free convex sets are known to be polyhedra. The precision…

Optimization and Control · Mathematics 2011-03-28 Gennadiy Averkov , Christian Wagner , Robert Weismantel

Let $K$ be a maximal lattice-free set in $\mathbb{R}^d$, that is, $K$ is convex and closed subset of $\mathbb{R}^d$, the interior of $K$ does not cointain points of $\mathbb{Z}^d$ and $K$ is inclusion-maximal with respect to the above…

Optimization and Control · Mathematics 2011-10-06 Gennadiy Averkov

A closed, convex set $K$ in $\mathbb{R}^2$ with non-empty interior is called lattice-free if the interior of $K$ is disjoint with $\mathbb{Z}^2$. In this paper we study the relation between the area and the lattice width of a planar…

Metric Geometry · Mathematics 2010-07-14 Gennadiy Averkov , Christian Wagner

We consider the problem of computing the maximal invariant set of discrete-time linear systems subject to a class of non-convex constraints that admit quadratic relaxations. These non-convex constraints include semialgebraic sets and other…

Systems and Control · Electrical Eng. & Systems 2020-11-30 Zheming Wang , Raphaël M. Jungers , Chong-Jin Ong

We introduce a generic technique to obtain linear relaxations of semidefinite programs with provable guarantees based on the commutativity of the constraint and the objective matrices. We study conditions under which the optimal value of…

Optimization and Control · Mathematics 2026-05-19 Daniel de Roux , Robert Carr , R. Ravi

A polyhedral convex set optimization problem is given by a set-valued objective mapping from the $n$-dimensional to the $q$-dimensional Euclidean space whose graph is a convex polyhedron. This problem can be seen as the most elementary…

Optimization and Control · Mathematics 2023-04-25 Niklas Hey , Andreas Löhne

We consider the question of which nonconvex sets can be represented exactly as the feasible sets of mixed-integer convex optimization problems. We state the first complete characterization for the case when the number of possible integer…

Optimization and Control · Mathematics 2017-06-20 Miles Lubin , Ilias Zadik , Juan Pablo Vielma

We prove that any complex analytic set in $\mathbb{C}^n$ which is Lipschitz normally embedded at infinity and has tangent cone at infinity that is a linear subspace of $\mathbb{C}^n$ must be an affine linear subspace of $\mathbb{C}^n$…

Algebraic Geometry · Mathematics 2018-03-07 Alexandre Fernandes , J. Edson Sampaio

Hermitian linear matrix pencils are ubiquitous in control theory, operator systems, semidefinite optimization, and real algebraic geometry. This survey reviews the fundamental features of the matricial solution set of a linear matrix…

Functional Analysis · Mathematics 2024-07-12 Jurij Volčič

We study a mixed integer linear program with m integer variables and k non-negative continuous variables in the form of the relaxation of the corner polyhedron that was introduced by Andersen, Louveaux, Weismantel and Wolsey [Inequalities…

Optimization and Control · Mathematics 2011-07-27 Amitabh Basu , Robert Hildebrand , Matthias Köppe

We consider an optimization problem in a convex space $E$ with an affine objective function, subject to $J$ constraints in the forms of inequalities on some other affine functions, where $J$ is a given nonnegative integer. Under suitable…

Optimization and Control · Mathematics 2023-05-11 Alexey Piunovskiy , Yi Zhang

We study the integrality gap of convex mixed-integer programs, that is, the difference between the optimal value of such a problem and the optimal value of its continuous relaxation. We study classes of convex sets whose associated…

Optimization and Control · Mathematics 2026-04-20 Burak Kocuk , Diego Moran Ramirez

Lattice-free gradient polyhedra can be used to certify optimality for mixed-integer convex minimization models. We consider how to construct these polyhedra for unconstrained models with two integer variables under the assumption that all…

Optimization and Control · Mathematics 2020-07-02 Joseph Paat , Miriam Schlöter , Emily Speakman

Maximal lattice free bodies are maximal polytopes without interior integral points. Scarf initiated the study of maximal lattice free bodies relative to the facet normals in a fixed matrix. In this paper we give an efficient algorithm for…

Combinatorics · Mathematics 2007-06-13 Anders Jensen , Niels Lauritzen , Bjarke Roune

Semidefinite programming is based on optimization of linear functionals over convex sets defined by linear matrix inequalities, namely, inequalities of the form $$L_A(X)=I-A_1X_1-\dots-A_g X_g\succeq0.$$ Here the $X_j$ are real numbers and…

Functional Analysis · Mathematics 2022-02-24 Eric Evert , Yi Fu , J. William Helton , John Yin

We describe all metric spaces that have sufficently many affine functions. As an application we obtain a metric characterization of linear-convex subsets of Banach spaces.

Metric Geometry · Mathematics 2013-04-25 Petra Schwer , Alexander Lytchak

Lattice-free sets (convex subsets of $\mathbb{R}^d$ without interior integer points) and their applications for cutting-plane methods in mixed-integer optimization have been studied in recent literature. Notably, the family of all integral…

Combinatorics · Mathematics 2015-09-18 Gennadiy Averkov , Jan Krümpelmann , Stefan Weltge

We study weighted Sobolev inequalities on open convex cones endowed with $\alpha$-homogeneous weights satisfying a certain concavity condition. We establish a so-called reduction principle for these inequalities and characterize optimal…

Functional Analysis · Mathematics 2025-07-11 Ladislav Drážný

The (matricial) solution set of a Linear Matrix Inequality (LMI) is a convex basic non-commutative semi-algebraic set. The main theorem of this paper is a converse, a result which has implications for both semidefinite programming and…

Functional Analysis · Mathematics 2011-08-31 J. William Helton , Scott McCullough
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