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.
Authors
- Minghao Yin (ORCID: https://orcid.org/0000-0002-6226-2394)
- Jiaxin Liang (ORCID: https://orcid.org/0009-0009-1031-4672)
- Junping Zhou (ORCID: https://orcid.org/0000-0002-6850-1237)
Institutions
- Northeast Normal University (CN)
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
Funders
- National Natural Science Foundation of China
- People's Government of Jilin Province