IJCAI 2021
Computing Optimal Hypertree Decompositions with SAT
Abstract
Hypertree width is a prominent hypergraph invariant with many algorithmic applications in constraint satisfaction and databases. We propose a novel characterization for hypertree width in terms of linear elimination orderings. We utilize this characterization to generate a new SAT encoding that we evaluate on an extensive set of benchmark instances. We compare it to state-of-the-art exact methods for computing optimal hypertree width. Our results show that the encoding based on the new characterization is not only significantly more compact than known encodings but also outperforms the other methods.
Authors
Keywords
Context
- Venue
- International Joint Conference on Artificial Intelligence
- Archive span
- 1969-2025
- Indexed papers
- 14525
- Paper id
- 566814629146234858