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This thesis investigates the extent to which the optimal value of a constraint satisfaction problem (CSP) can be approximated by some sentence of fixed point logic with counting (FPC). It is known that, assuming $\mathsf{P} \neq…

Logic in Computer Science · Computer Science 2020-08-10 Jamie Tucker-Foltz

This article investigates the approximation quality achievable for biobjective minimization problems with respect to the Pareto cone by solutions that are (approximately) optimal with respect to larger ordering cones. When simultaneously…

Optimization and Control · Mathematics 2021-09-22 Arne Herzel , Stephan Helfrich , Stefan Ruzika , Clemens Thielen

We prove explicit approximation hardness results for the Graphic TSP on cubic and subcubic graphs as well as the new inapproximability bounds for the corresponding instances of the (1,2)-TSP. The proof technique uses new modular…

Computational Complexity · Computer Science 2013-05-15 Marek Karpinski , Richard Schmied

The success of Constraint Programming relies partly on the global constraints and implementation of the associated filtering algorithms. Recently, new ideas emerged to improve these implementations in practice, especially regarding the all…

Artificial Intelligence · Computer Science 2025-02-06 Margaux Schmied , Jean-Charles Regin

In this paper, we continue the study of robust satisfiability of promise CSPs (PCSPs), initiated in (Brakensiek, Guruswami, Sandeep, STOC 2023 / Discrete Analysis 2025), and obtain the following results: For the PCSP 1-in-3-SAT vs NAE-SAT…

Data Structures and Algorithms · Computer Science 2026-02-12 Joshua Brakensiek , Lorenzo Ciardo , Venkatesan Guruswami , Aaron Potechin , Stanislav Živný

In this paper we design a new primal-dual algorithm for the classic discrete optimization problem of maximizing a monotone submodular function subject to a cardinality constraint achieving the optimal approximation of $(1-1/e)$. This…

Data Structures and Algorithms · Computer Science 2023-11-15 Deeparnab Chakrabarty , Luc Cote

A dominating set D in a graph G is a subset of its vertices such that every vertex of the graph which does not belong to set D is adjacent to at least one vertex from set D. A set of vertices of graph G is a global dominating set if it is a…

Discrete Mathematics · Computer Science 2024-10-25 Ernesto Parra Inza , Nodari Vakhania , Jose M. Sigarreta Almira , Frank A. Hernández Mira

In this paper, we introduce an exact algorithm with a time complexity of $O^*(1.325^m)$ for the {\sc weighted mutually exclusive maximum set cover} problem, where $m$ is the number of subsets in the problem. This is an NP-hard motivated and…

Data Structures and Algorithms · Computer Science 2014-01-27 Songjian Lu , Xinghua Lu

An instance of the Connected Maximum Cut problem consists of an undirected graph G = (V, E) and the goal is to find a subset of vertices S $\subseteq$ V that maximizes the number of edges in the cut \delta(S) such that the induced graph…

Data Structures and Algorithms · Computer Science 2015-07-03 MohammadTaghi Hajiaghayi , Guy Kortsarz , Robert MacDavid , Manish Purohit , Kanthi Sarpatwar

We show that any submodular minimization (SM) problem defined on a linear constraint set with constraints having up to two variables per inequality, are 2-approximable in polynomial time. If the constraints are monotone (the two variables…

Discrete Mathematics · Computer Science 2017-05-01 Dorit S. Hochbaum

This paper is about minimum cost constrained selection of inputs and outputs for generic arbitrary pole placement. The input-output set is constrained in the sense that the set of states that each input can influence and the set of states…

Optimization and Control · Mathematics 2018-01-11 Shana Moothedath , Prasanna Chaporkar , Madhu N. Belur

We present several novel encodings for cardinality constraints, which use fewer clauses than previous encodings and, more importantly, introduce new generally applicable techniques for constructing compact encodings. First, we present a CNF…

Computational Complexity · Computer Science 2026-04-20 Andrew Krapivin , Benjamin Przybocki , Bernardo Subercaseaux

Let $G$ be a graph. A dominating set $D\subseteq V(G)$ is a super dominating set if for every vertex $x\in V(G) \setminus D$ there exists $y\in D$ such that $N_G(y)\cap (V(G)\setminus D)) = \{x\}$. The cardinality of a smallest super…

Combinatorics · Mathematics 2023-02-20 Csilla Bujtás , Nima Ghanbari , Sandi Klavžar

An instance of Max CSP is a finite collection of constraints on a set of variables, and the goal is to assign values to the variables that maximises the number of satisfied constraints. Max CSP captures many well-known problems (such as Max…

Computational Complexity · Computer Science 2007-12-11 Peter Jonsson , Andrei Krokhin , Fredrik Kuivinen

Given a graph $G=(V, E)$ and a positive integer $k$, in Maximum $k$-Order Bounded Component Set (Max-$k$-OBCS), it is required to find a vertex set $S \subseteq V$ of maximum size such that each component in the induced graph $G[S]$ has at…

Data Structures and Algorithms · Computer Science 2018-03-29 Sounaka Mishra , Shijin Rajakrishnan

In the Max $k$-Weight SAT (aka Max SAT with Cardinality Constraint) problem, we are given a CNF formula with $n$ variables and $m$ clauses together with a positive integer $k$. The goal is to find an assignment where at most $k$ variables…

Data Structures and Algorithms · Computer Science 2024-06-05 Pasin Manurangsi

One of the classic results in scheduling theory is the 2-approximation algorithm by Lenstra, Shmoys, and Tardos for the problem of scheduling jobs to minimize makespan on unrelated machines, i.e., job j requires time p_{ij} if processed on…

Data Structures and Algorithms · Computer Science 2011-03-22 Ola Svensson

The vertex cover problem is a famous combinatorial problem, and its complexity has been heavily studied. While a 2-approximation can be trivially obtained for it, researchers have not been able to approximate it better than 2-\textit{o}(1).…

Computational Complexity · Computer Science 2025-03-04 Majid Zohrehbandian

A common interpretation of soft constraints penalizes the database for every violation of every constraint, where the penalty is the cost (weight) of the constraint. A computational challenge is that of finding an optimal subset: a…

Databases · Computer Science 2020-09-30 Nofar Carmeli , Martin Grohe , Benny Kimelfeld , Ester Livshits , Muhammad Tibi

We consider the problem of finding a spanning tree with maximum number of leaves (MaxLeaf). A 2-approximation algorithm is known for this problem, and a 3/2-approximation algorithm when restricted to graphs where every vertex has degree 3…

Discrete Mathematics · Computer Science 2009-12-02 Paul Bonsma