A SAT Approach to Branchwidth

Abstract

Branch decomposition is a prominent method for structurally decomposing a graph, hypergraph or CNF formula. The width of a branch decomposition provides a measure of how well the object is decomposed. For many applications it is crucial to compute a branch decomposition whose width is as small as possible. We propose a SAT approach to finding branch decompositions of small width. The core of our approach is an efficient SAT encoding which determines with a single SAT-call whether a given hypergraph admits a branch decomposition of certain width. For our encoding we develop a novel partition-based characterization of branch decompositions. The encoding size imposes a limit on the size of the given hypergraph. In order to break through this barrier and to scale the SAT approach to larger instances, we develop a new heuristic approach where the SAT encoding is used to locally improve a given candidate decomposition until a fixed-point is reached. This new method scales now to instances with several thousands of vertices and edges.

Cite

Text

Lodha et al. "A SAT Approach to Branchwidth." International Joint Conference on Artificial Intelligence, 2017. doi:10.24963/IJCAI.2017/689

Markdown

[Lodha et al. "A SAT Approach to Branchwidth." International Joint Conference on Artificial Intelligence, 2017.](https://mlanthology.org/ijcai/2017/lodha2017ijcai-sat/) doi:10.24963/IJCAI.2017/689

BibTeX

@inproceedings{lodha2017ijcai-sat,
  title     = {{A SAT Approach to Branchwidth}},
  author    = {Lodha, Neha and Ordyniak, Sebastian and Szeider, Stefan},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2017},
  pages     = {4894-4898},
  doi       = {10.24963/IJCAI.2017/689},
  url       = {https://mlanthology.org/ijcai/2017/lodha2017ijcai-sat/}
}