DiverSAT: A Novel and Effective Local Search Algorithm for Diverse SAT Problem

For many real-world problems, users are often interested not only in finding a single solution but in obtaining a sufficiently diverse collection of solutions. In this work, we consider the Diverse SAT problem, aiming to find a set of diverse satisfying assignments for a given propositional formula. We propose a novel and effective local search algorithm, DiverSAT, to solve the problem. To cope with diversity, we introduce three heuristics and a perturbation strategy based on some relevant information. We conduct extensive experiments on a large number of public benchmarks, collected from semiformal hardware verification, logistics planning, and other domains. The results show that DiverSAT outperforms the existing algorithms on most of these benchmarks.

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Publication Details

Journal
Proceedings of the AAAI Conference on Artificial Intelligence
Published
2025-04-11
DOI
https://doi.org/10.1609/aaai.v39i11.33228
Citations
1
Primary Topic
Constraint Satisfaction and Optimization
Type
article
Field-Weighted Citation Impact
1.68

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article

DiverSAT: A Novel and Effective Local Search Algorithm for Diverse SAT Problem

Minghao Yin, Jiaxin Liang, Junping Zhou
1 citations
Proceedings of the AAAI Conference on Artificial Intelligence
Constraint Satisfaction and Optimization
1.68
article

DiverSAT: A Novel and Effective Local Search Algorithm for Diverse SAT Problem

Minghao Yin, Jiaxin Liang, Junping Zhou
article en
1 citations

Abstract

For many real-world problems, users are often interested not only in finding a single solution but in obtaining a sufficiently diverse collection of solutions. In this work, we consider the Diverse SAT problem, aiming to find a set of diverse satisfying assignments for a given propositional formula. We propose a novel and effective local search algorithm, DiverSAT, to solve the problem. To cope with diversity, we introduce three heuristics and a perturbation strategy based on some relevant information. We conduct extensive experiments on a large number of public benchmarks, collected from semiformal hardware verification, logistics planning, and other domains. The results show that DiverSAT outperforms the existing algorithms on most of these benchmarks.

Proceedings of the AAAI Conference on Artificial IntelligenceVol. 39(11)
Northeast Normal University (CN)
National Natural Science Foundation of China, People's Government of Jilin Province
Openalex Percentile: Top 13%
Constraint Satisfaction and Optimization
1.68
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