An Improved Algorithm for Sparse Instances of SAT

Fuente: arXiv
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Main Authors: Jain, Sanjay, Neoh, Tzeh Yuan, Stephan, Frank
Format: Preprint
Published: 2024
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author Jain, Sanjay
Neoh, Tzeh Yuan
Stephan, Frank
author_facet Jain, Sanjay
Neoh, Tzeh Yuan
Stephan, Frank
contents We show that the CNF satisfiability problem (SAT) can be solved in time $O^*(1.1199^{(d-2)n})$, where $d$ is either the maximum number of occurrences of any variable or the average number of occurrences of all variables if no variable occurs only once. This improves upon the known upper bound of $O^*(1.1279^{(d-2)n})$ by Wahlstr$\ddot{\text{o}}$m (SAT 2005) and $O^*(1.1238^{(d-2)n})$ by Peng and Xiao (IJCAI 2023). For $d\leq 4$, our algorithm is better than previous results. Our main technical result is an algorithm that runs in $O^*(1.1199^n)$ for 3-occur-SAT, a restricted instance of SAT where all variables have at most 3 occurrences. Through deeper case analysis and a reduction rule that allows us to resolve many variables under a relatively broad criteria, we are able to circumvent the bottlenecks in previous algorithms.
format Preprint
id arxiv_https___arxiv_org_abs_2411_07389
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle An Improved Algorithm for Sparse Instances of SAT
Jain, Sanjay
Neoh, Tzeh Yuan
Stephan, Frank
Data Structures and Algorithms
We show that the CNF satisfiability problem (SAT) can be solved in time $O^*(1.1199^{(d-2)n})$, where $d$ is either the maximum number of occurrences of any variable or the average number of occurrences of all variables if no variable occurs only once. This improves upon the known upper bound of $O^*(1.1279^{(d-2)n})$ by Wahlstr$\ddot{\text{o}}$m (SAT 2005) and $O^*(1.1238^{(d-2)n})$ by Peng and Xiao (IJCAI 2023). For $d\leq 4$, our algorithm is better than previous results. Our main technical result is an algorithm that runs in $O^*(1.1199^n)$ for 3-occur-SAT, a restricted instance of SAT where all variables have at most 3 occurrences. Through deeper case analysis and a reduction rule that allows us to resolve many variables under a relatively broad criteria, we are able to circumvent the bottlenecks in previous algorithms.
title An Improved Algorithm for Sparse Instances of SAT
topic Data Structures and Algorithms
url https://arxiv.org/abs/2411.07389