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Every definite logic program has as its meaning a least Herbrand model with respect to the program-independent ordering "set-inclusion". In the case of normal logic programs there do not exist least models in general. However, according to…

Logic in Computer Science · Computer Science 2011-09-01 Rainer Lüdecke

We discuss here constraint programming (CP) by using a proof-theoretic perspective. To this end we identify three levels of abstraction. Each level sheds light on the essence of CP. In particular, the highest level allows us to bring CP…

Programming Languages · Computer Science 2007-05-23 Krzysztof R. Apt

A semilinear relation is a finite union of finite intersections of open and closed half-spaces over, for instance, the reals, the rationals, or the integers. Semilinear relations have been studied in connection with algebraic geometry,…

Computational Complexity · Computer Science 2015-06-02 Peter Jonsson , Johan Thapper

Consider an algorithm computing in a differential field with several commuting derivations such that the only operations it performs with the elements of the field are arithmetic operations, differentiation, and zero testing. We show that,…

Commutative Algebra · Mathematics 2021-08-31 Wei Li , Alexey Ovchinnikov , Gleb Pogudin , Thomas Scanlon

We study the complexity of identifying the integer feasibility of reverse convex sets. We present various settings where the complexity can be either NP-Hard or efficiently solvable when the dimension is fixed. Of particular interest is the…

Optimization and Control · Mathematics 2024-09-10 Robert Hildebrand , Adrian Göß

We consider the class of packing integer programs (PIPs) that are column sparse, i.e. there is a specified upper bound k on the number of constraints that each variable appears in. We give an (ek+o(k))-approximation algorithm for k-column…

Data Structures and Algorithms · Computer Science 2015-05-13 Nikhil Bansal , Nitish Korula , Viswanath Nagarajan , Aravind Srinivasan

Advancements in mathematical programming have made it possible to efficiently tackle large-scale real-world problems that were deemed intractable just a few decades ago. However, provably optimal solutions may not be accepted due to the…

Optimization and Control · Mathematics 2023-12-22 Kevin-Martin Aigner , Marc Goerigk , Michael Hartisch , Frauke Liers , Arthur Miehlich

For general quadratically-constrained quadratic programming (QCQP), we propose a parabolic relaxation described with convex quadratic constraints. An interesting property of the parabolic relaxation is that the original non-convex feasible…

Optimization and Control · Mathematics 2022-08-09 Ramtin Madani , Mersedeh Ashraphijuo , Mohsen Kheirandishfard , Alper Atamturk

There are numerous ways to represent real numbers. We may use, e.g., Cauchy sequences, Dedekind cuts, numerical base-10 expansions, numerical base-2 expansions and continued fractions. If we work with full Turing computability, all these…

Logic · Mathematics 2020-03-30 Ivan Georgiev , Lars Kristiansen , Frank Stephan

A classic result of Cook et al. (1986) bounds the distances between optimal solutions of mixed-integer linear programs and optimal solutions of the corresponding linear relaxations. Their bound is given in terms of the number of variables…

Optimization and Control · Mathematics 2018-01-29 Joseph Paat , Robert Weismantel , Stefan Weltge

Inductive logic programming (ILP) is a form of logical machine learning. The goal is to search a hypothesis space for a hypothesis that generalises training examples and background knowledge. We introduce an approach that 'shrinks' the…

Artificial Intelligence · Computer Science 2026-05-18 Andrew Cropper , Filipe Gouveia , David M. Cerna

This work connects two mathematical fields - computational complexity and interval linear algebra. It introduces the basic topics of interval linear algebra - regularity and singularity, full column rank, solving a linear system, deciding…

Computational Complexity · Computer Science 2016-02-02 Jaroslav Horáček , Milan Hladík , Michal Černý

We investigate algebraic and arithmetic properties of a class of sequences of sparse polynomials that have binomial coefficients both as exponents and as coefficients. In addition to divisibility and irreducibility results we also consider…

Number Theory · Mathematics 2021-09-27 Karl Dilcher , Maciej Ulas

A type system is introduced for a generic Object Oriented programming language in order to infer resource upper bounds. A sound andcomplete characterization of the set of polynomial time computable functions is obtained. As a consequence,…

Programming Languages · Computer Science 2018-02-20 Emmanuel Hainry , Romain Péchoux

Lagrangian Relaxation (LR) is a powerful technique for solving large-scale Mixed Integer Linear Programming (MILP), particularly those with decomposable structures, such as vehicle routing or unit commitment problems. By relaxing the…

Machine Learning · Statistics 2026-05-27 Tung Quoc Le , Anh Tuan Nguyen , Viet Anh Nguyen

We give an exact algorithm for the 0-1 Integer Linear Programming problem with a linear number of constraints that improves over exhaustive search by an exponential factor. Specifically, our algorithm runs in time…

Computational Complexity · Computer Science 2014-02-20 Russell Impagliazzo , Shachar Lovett , Ramamohan Paturi , Stefan Schneider

An integer program is called ideal if its continuous relaxation coincides with its convex hull allowing the problem to be solved as a continuous program and offering substantial computational advantages. Proving idealness analytically can…

Optimization and Control · Mathematics 2026-01-22 Jamie Fravel , Robert Hildebrand

Many papers in the field of integer linear programming (ILP, for short) are devoted to problems of the type $\max\{c^\top x \colon A x = b,\, x \in \mathbb{Z}^n_{\geq 0}\}$, where all the entries of $A,b,c$ are integer, parameterized by the…

Computational Complexity · Computer Science 2022-11-30 D. V. Gribanov , I. A. Shumilov , D. S. Malyshev , P. M. Pardalos

Humans can observe a single, imperfect demonstration and immediately generalize to very different problem settings. Robots, in contrast, often require hundreds of examples and still struggle to generalize beyond the training conditions. We…

Robotics · Computer Science 2025-08-13 Ben Zandonati , Tomás Lozano-Pérez , Leslie Pack Kaelbling

Programs with floating-point computations are often derived from mathematical models or designed with the semantics of the real numbers in mind. However, for a given input, the computed path with floating-point numbers may differ from the…

Programming Languages · Computer Science 2016-08-08 Hélène Collavizza , Claude Michel , Michel Rueher