Satisfiability to Coverage in Presence of Fairness, Matroid, and Global Constraints

Tanmay Inamdar, Pallavi Jain, Daniel Lokshtanov, Abhishek Sahu, Saket Saurabh, Anannya Upasana

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

In the MaxSAT with Cardinality Constraint problem (CC-MaxSAT), we are given a CNF-formula Φ, and a positive integer k, and the goal is to find an assignment β with at most k variables set to true (also called a weight k-assignment) such that the number of clauses satisfied by β is maximized. Maximum Coverage can be seen as a special case of CC-MaxSat, where the formula Φ is monotone, i.e., does not contain any negative literals. CC-MaxSat and Maximum Coverage are extremely well-studied problems in the approximation algorithms as well as the parameterized complexity literature. Our first conceptual contribution is that CC-MaxSat and Maximum Coverage are equivalent to each other in the context of FPT-Approximation parameterized by k (here, the approximation is in terms of the number of clauses satisfied/elements covered). In particular, we give a randomized reduction from CC-MaxSat to Maximum Coverage running in time O(1/ϵ)k · (m + n)O(1) that preserves the approximation guarantee up to a factor of (1 − ϵ). Furthermore, this reduction also works in the presence of “fairness” constraints on the satisfied clauses, as well as matroid constraints on the set of variables that are assigned true. Here, the “fairness” constraints are modeled by partitioning the clauses of the formula Φ into r different colors, and the goal is to find an assignment that satisfies at least tj clauses of each color 1 ≤ j ≤ r. Armed with this reduction, we focus on designing FPT-Approximation schemes (FPT-ASes) for Maximum Coverage and its generalizations. Our algorithms are based on a novel combination of a variety of ideas, including a carefully designed probability distribution that exploits sparse coverage functions. These algorithms substantially generalize the results in Jain et al. [SODA 2023] for CC-MaxSat and Maximum Coverage for Kd,d-free set systems (i.e., no d sets share d elements), as well as a recent FPT-AS for Matroid Constrained Maximum Coverage by Sellier [ESA 2023] for frequency-d set systems.

Original languageEnglish
Title of host publication51st International Colloquium on Automata, Languages, and Programming, ICALP 2024
EditorsKarl Bringmann, Martin Grohe, Gabriele Puppis, Ola Svensson
PublisherSchloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing
ISBN (Electronic)9783959773225
DOIs
StatePublished - 1 Jul 2024
Externally publishedYes
Event51st International Colloquium on Automata, Languages, and Programming, ICALP 2024 - Tallinn, Estonia
Duration: 8 Jul 202412 Jul 2024

Publication series

NameLeibniz International Proceedings in Informatics, LIPIcs
Volume297
ISSN (Print)1868-8969

Conference

Conference51st International Colloquium on Automata, Languages, and Programming, ICALP 2024
Country/TerritoryEstonia
CityTallinn
Period8/07/2412/07/24

Keywords

  • FPT Approximation
  • Matroids
  • Max SAT
  • Partial Vertex Cover

ASJC Scopus subject areas

  • Software

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