Combining differing solution approaches by means of solver portfolios has proven as a highly effective technique for boosting solver performance. We consider the problem of generating parallel SAT solver portfolios. Our approach is based on a recently introduced sequential SAT solver portfolio that excelled at the last SAT competition. We show how the approach can be generalized for the paralle...

The propositional satisfiability (SAT) problem is one of the most fundamental problems in computer science. SAT solvers have been successfully applied to a wide range of practical applications, including hardware model checking, software model finding, equivalence checking, and planning, among many others. Empirical research has been very fruitful for the development of efficient methods for SA...

We analyze, in this work, the performance of a recently introduced weighted Max-SAT solver, Clone, in the Max-SAT evaluation 2007. Clone utilizes a novel bound computation based on formula compilation that allows it to search in a reduced search space. We study how additional techniques from the SAT and Max-SAT literature affect the performance of Clone on problems from the evaluation. We then ...

We analyze to what extent the random SAT and Max-SAT problems differ in their properties. Our findings suggest that for random k-CNF with ratio in a certain range, Max-SAT can be solved by any SAT algorithm with subexponential slowdown, while for formulae with ratios greater than some constant, algorithms under the random walk framework require substantially different heuristics. In light of th...

We present a partial Max-SAT solver QMaxSAT which uses CNF encoding of Boolean cardinality constraints. The old version 0.1 was obtained by adapting a CDCL based SAT solver MiniSat to manage cardinality constraints. It was placed first in the industrial subcategory and second in the crafted subcategory of partial Max-SAT category of the 2010 Max-SAT Evaluation. The new version 0.2 is obtained b...

In recent years there has been signi1cant interest in the study of random k-SAT formulae. For a given set of n Boolean variables, let Bk denote the set of all possible disjunctions of k distinct, non-complementary literals from its variables (k-clauses). A random k-SAT formula Fk(n; m) is formed by selecting uniformly and independently m clauses from Bk and taking their conjunction. Motivated b...

Exact Max-SAT solvers, compared with SAT solvers, apply little inference at each node of the proof tree. Commonly used SAT inference rules like unit propagation produce a simplified formula that preserves satisfiability but, unfortunately, solving the Max-SAT problem for the simplified formula is not equivalent to solving it for the original formula. In this paper, we define a number of origina...

For a fixed graph H, a graph G is H-saturated if there is no copy of H in G, but for any edge e 6∈ G, there is a copy of H in G + e. The collection of Hsaturated graphs of order n is denoted by SAT(n,H), and the saturation number, sat(n,H), is the minimum number of edges in a graph in SAT(n,H). Let Tk be a tree on k vertices. The saturation numbers sat(n, Tk) for some families of trees will be ...

The success of portfolio approaches in SAT solving relies on the observation that different SAT solvers may dramatically change their performance depending on the class of SAT instances they are trying to solve. In these approaches, a set of features of the problem is used to build a prediction model, which classifies instances into classes, and computes the fastest algorithm to solve each of t...

Boolean SATisfiability (SAT) is an important problem in AI. SAT solvers have been effectively used in important industrial applications including automated planning and verification. In this paper, we present novel algorithms for fast SAT solving by employing two common subclause elimination (CSE) approaches. Our motivation is that modern SAT solving techniques can be more efficient on CSE-proc...