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IJCAI 2021

Computing Optimal Hypertree Decompositions with SAT

Conference Paper Constraints and SAT Artificial Intelligence

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

  • Constraints and SAT: Constraint Satisfaction
  • Constraints and SAT: Constraints: Modeling, Solvers, Applications
  • Constraints and SAT: Satisfiability Modulo Theories

Context

Venue
International Joint Conference on Artificial Intelligence
Archive span
1969-2025
Indexed papers
14525
Paper id
566814629146234858
v2026.09.13