Improved Exact Solver for the Weighted MAX-SAT Problem

13 pages•Published: May 15, 2012

Abstract

Many exact Max-SAT solvers use a branch and bound algorithm, where the lower bound is calculated with a combination of Max-SAT resolution and detection of disjoint inconsistent subformulas. We propose a propagation algorithm which improves the detection of disjoint inconsistent subformulas compared to algorithms previously used in Max-SAT solvers. We implemented this algorithm in our new solver akmaxsat and compared our solver with three solvers using unit propagation and restricted failed literal detection; these solvers are currently state-of-the-art on random Max-SAT instances. We also developed a lazy deletion data structure for our solver which speeds up lower bound calculation on instances with a high clauses-to-variables ratio. Our experiments show that our solver runs faster than the previously best solvers on randomly generated instances with a high clauses-to-variables ratio.

Keyphrases: data structure, maximum satisfiability, propagation algorithm

In: Daniel Le Berre (editor). POS-10. Pragmatics of SAT, vol 8, pages 15-27.

Links:	https://easychair.org/publications/paper/p3wf
	https://doi.org/10.29007/38lm

BibTeX entry

@inproceedings{POS-10:Improved_Exact_Solver_Weighted,
  author    = {Adrian Kuegel},
  title     = {Improved Exact Solver for the Weighted MAX-SAT Problem},
  booktitle = {POS-10. Pragmatics of SAT},
  editor    = {Daniel Le Berre},
  series    = {EPiC Series in Computing},
  volume    = {8},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-7340},
  url       = {/publications/paper/p3wf},
  doi       = {10.29007/38lm},
  pages     = {15-27},
  year      = {2012}}

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