Flow-augmentation III: Complexity dichotomy for Boolean CSPs parameterized by the number of unsatisfied constraints

July 15, 2022 ยท The Ethereal ยท ๐Ÿ› ACM-SIAM Symposium on Discrete Algorithms

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Authors Eun Jung Kim, Stefan Kratsch, Marcin Pilipczuk, Magnus Wahlstrรถm arXiv ID 2207.07422 Category cs.CC: Computational Complexity Cross-listed cs.DS Citations 14 Venue ACM-SIAM Symposium on Discrete Algorithms Last Checked 1 month ago
Abstract
We study the parameterized problem of satisfying ``almost all'' constraints of a given formula $F$ over a fixed, finite Boolean constraint language $ฮ“$, with or without weights. More precisely, for each finite Boolean constraint language $ฮ“$, we consider the following two problems. In Min SAT$(ฮ“)$, the input is a formula $F$ over $ฮ“$ and an integer $k$, and the task is to find an assignment $ฮฑ\colon V(F) \to \{0,1\}$ that satisfies all but at most $k$ constraints of $F$, or determine that no such assignment exists. In Weighted Min SAT$(ฮ“$), the input additionally contains a weight function $w \colon F \to \mathbb{Z}_+$ and an integer $W$, and the task is to find an assignment $ฮฑ$ such that (1) $ฮฑ$ satisfies all but at most $k$ constraints of $F$, and (2) the total weight of the violated constraints is at most $W$. We give a complete dichotomy for the fixed-parameter tractability of these problems: We show that for every Boolean constraint language $ฮ“$, either Weighted Min SAT$(ฮ“)$ is FPT; or Weighted Min SAT$(ฮ“)$ is W[1]-hard but Min SAT$(ฮ“)$ is FPT; or Min SAT$(ฮ“)$ is W[1]-hard. This generalizes recent work of Kim et al. (SODA 2021) which did not consider weighted problems, and only considered languages $ฮ“$ that cannot express implications $(u \to v)$ (as is used to, e.g., model digraph cut problems). Our result generalizes and subsumes multiple previous results, including the FPT algorithms for Weighted Almost 2-SAT, weighted and unweighted $\ell$-Chain SAT, and Coupled Min-Cut, as well as weighted and directed versions of the latter. The main tool used in our algorithms is the recently developed method of directed flow-augmentation (Kim et al., STOC 2022).
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