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We use exact enumeration to characterize the solutions of quadratic unconstrained binary optimization problems of less than 21 variables in terms of their distributions of Hamming distances to close-by solutions. We also perform experiments…

Quantum Physics · Physics 2025-11-04 Vrinda Mehta , Fengping Jin , Kristel Michielsen , Hans De Raedt

The convex hull describes the extent or shape of a set of data and is used ubiquitously in computational geometry. Common algorithms to construct the convex hull on a finite set of n points (x,y) range from O(nlogn) time to O(n) time.…

Computational Geometry · Computer Science 2015-05-06 José O. Cadenas , Graham Megson

As a contribution to quantitative set-theoretic inferencing, a translation is proposed of conjunctions of literals of the forms $x=y\setminus z$, $x \neq y\setminus z$, and $z =\{x\}$, where $x,y,z$ stand for variables ranging over the von…

Logic in Computer Science · Computer Science 2022-11-15 Domenico Cantone , Andrea De Domenico , Pietro Maugeri , Eugenio G. Omodeo

The problem of minimizing a (nonconvex) quadratic form over the unit simplex, referred to as a standard quadratic program, admits an exact convex conic formulation over the computationally intractable cone of completely positive matrices.…

Optimization and Control · Mathematics 2020-03-02 Y. Gorkem Gokmen , E. Alper Yildirim

A set in the Euclidean plane is said to be biconvex if, for some angle $\theta\in[0,\pi/2)$, all its sections along straight lines with inclination angles $\theta$ and $\theta+\pi/2$ are convex sets (i.e, empty sets or segments).…

Statistics Theory · Mathematics 2020-06-23 Alejandro Cholaquidis , Antonio Cuevas

The Quadratic Unconstrained Binary Optimization problem (QUBO) has become a unifying model for representing a wide range of combinatorial optimization problems, and for linking a variety of disciplines that face these problems. A new class…

Artificial Intelligence · Computer Science 2017-05-30 Mark Lewis , Fred Glover

The paper studies a class of quadratic optimal control problems for partially observable linear dynamical systems. In contrast to the full information case, the control is required to be adapted to the filtration generated by the…

Optimization and Control · Mathematics 2022-03-01 Jingrui Sun , Jie Xiong

We present a novel and effective binary representation for convex shapes. We show the equivalence between the shape convexity and some properties of the associated indicator function. The proposed method has two advantages. Firstly, the…

Numerical Analysis · Mathematics 2020-02-25 Shousheng Luo , Xue-Cheng Tai , Yang Wang

The Birkhoff polytope (the convex hull of the set of permutation matrices) is frequently invoked in formulating relaxations of optimization problems over permutations. The Birkhoff polytope is represented using $\Theta(n^2)$ variables and…

Optimization and Control · Mathematics 2016-02-16 Cong Han Lim , Stephen J. Wright

Variational analysis provides the theoretical foundations and practical tools for constructing optimization algorithms without being restricted to smooth or convex problems. We survey the central concepts in the context of a concrete but…

Optimization and Control · Mathematics 2025-04-08 Johannes O. Royset

In this paper, we consider the problem of multi-objective optimal control of a dynamical system with additive and multiplicative noises with given second moments and arbitrary probability distributions. The objectives are given by quadratic…

Optimization and Control · Mathematics 2014-02-17 Ather Gattami

Optimization problems with convex quadratic cost and polyhedral constraints are ubiquitous in signal processing, automatic control and decision-making. We consider here an enlarged problem class that allows to encode logical conditions and…

Optimization and Control · Mathematics 2026-04-09 Alberto De Marchi

Combinatorial optimization problems are typically formulated using Quadratic Unconstrained Binary Optimization (QUBO), where constraints are enforced through penalty terms that introduce auxiliary variables and rapidly increase Hamiltonian…

Quantum Physics · Physics 2026-02-10 Shashank Sanjay Bhat , Peiyong Wang , Joseph West , Udaya Parampalli

Quadratic invariance is a condition which has been shown to allow for optimal decentralized control problems to be cast as convex optimization problems. The condition relates the constraints that the decentralization imposes on the…

Optimization and Control · Mathematics 2011-09-29 Michael C. Rotkowitz , Nuno C. Martins

Constrained optimization problems appear in a wide variety of challenging real-world problems, where constraints often capture the physics of the underlying system. Classic methods for solving these problems rely on iterative algorithms…

Systems and Control · Electrical Eng. & Systems 2023-06-13 Meiyi Li , Soheil Kolouri , Javad Mohammadi

In optimization problems involving smooth functions and real and matrix variables, that contain matrix semidefiniteness constraints, consider the following change of variables: Replace the positive semidefinite matrix $X \in \mathbb{S}^d$,…

Optimization and Control · Mathematics 2025-02-05 Lijun Ding , Stephen J. Wright

Convex hulls are a fundamental geometric tool used in a number of algorithms. A famous paper by Akl and Toussaint in 1978 described a way to reduce the number of points involved in the computation, which is since known as the Akl-Toussaint…

Computational Geometry · Computer Science 2013-04-10 Jean Souviron

We study MINLO (mixed-integer nonlinear optimization) formulations of the disjunction $x\in\{0\}\cup[l,u]$, where $z$ is a binary indicatorof $x\in[l,u]$ ($u> \ell > 0$), and $y$ "captures" $f(x)$, which is assumed to be convex on its…

Optimization and Control · Mathematics 2020-01-07 Jon Lee , Daphne Skipper , Emily Speakman

The quadratic system provided by the Time of Arrival technique can be solved analytically or by optimization algorithms. In practice, a combination of both methods is used. An important problem in quadratic optimization is the possible…

Optimization and Control · Mathematics 2018-01-11 Juri Sidorenko , Leo Doktorski , Volker Schatz , Norbert Scherer-Negenborn , Michael Arens

Particle swarm optimization is used in several combinatorial optimization problems. In this work, particle swarms are used to solve quadratic programming problems with quadratic constraints. The approach of particle swarms is an example for…

Artificial Intelligence · Computer Science 2014-07-24 Deepak Kumar , A G Ramakrishnan