1,533 research outputs found
The Connectivity of Boolean Satisfiability: Computational and Structural Dichotomies
Boolean satisfiability problems are an important benchmark for questions
about complexity, algorithms, heuristics and threshold phenomena. Recent work
on heuristics, and the satisfiability threshold has centered around the
structure and connectivity of the solution space. Motivated by this work, we
study structural and connectivity-related properties of the space of solutions
of Boolean satisfiability problems and establish various dichotomies in
Schaefer's framework.
On the structural side, we obtain dichotomies for the kinds of subgraphs of
the hypercube that can be induced by the solutions of Boolean formulas, as well
as for the diameter of the connected components of the solution space. On the
computational side, we establish dichotomy theorems for the complexity of the
connectivity and st-connectivity questions for the graph of solutions of
Boolean formulas. Our results assert that the intractable side of the
computational dichotomies is PSPACE-complete, while the tractable side - which
includes but is not limited to all problems with polynomial time algorithms for
satisfiability - is in P for the st-connectivity question, and in coNP for the
connectivity question. The diameter of components can be exponential for the
PSPACE-complete cases, whereas in all other cases it is linear; thus, small
diameter and tractability of the connectivity problems are remarkably aligned.
The crux of our results is an expressibility theorem showing that in the
tractable cases, the subgraphs induced by the solution space possess certain
good structural properties, whereas in the intractable cases, the subgraphs can
be arbitrary
Incremental Cardinality Constraints for MaxSAT
Maximum Satisfiability (MaxSAT) is an optimization variant of the Boolean
Satisfiability (SAT) problem. In general, MaxSAT algorithms perform a
succession of SAT solver calls to reach an optimum solution making extensive
use of cardinality constraints. Many of these algorithms are non-incremental in
nature, i.e. at each iteration the formula is rebuilt and no knowledge is
reused from one iteration to another. In this paper, we exploit the knowledge
acquired across iterations using novel schemes to use cardinality constraints
in an incremental fashion. We integrate these schemes with several MaxSAT
algorithms. Our experimental results show a significant performance boost for
these algo- rithms as compared to their non-incremental counterparts. These
results suggest that incremental cardinality constraints could be beneficial
for other constraint solving domains.Comment: 18 pages, 4 figures, 1 table. Final version published in Principles
and Practice of Constraint Programming (CP) 201
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