In this technical report we briefly describe the instances submitted to the 2006 and 2007 Max-SAT Evaluations. First, we introduce the instances that can be directly encoded as Max-SAT. Then, we describe the methods used to translate problem instances coming from other optimization frameworks to Max-SAT. Finally, we present a quick reference table containing short descriptions of each set of pr...

We study the relationship between optimal planning algorithms, in the form of (iterative deepening) A∗ with (forward) state-space search, and the reduction of the problem to SAT. Our results establish a strict dominance relation between the two approaches: any iterative deepening A∗ search can be efficiently simulated in the SAT framework, assuming that the heuristic has been encoded in the SAT...

MUMCUT is a criterion for testing Boolean specifications. The traditional test case generation methods for this problem are based on approximate approaches. The efficiency of these algorithms depend on the designers’ experience on this coverage. In this paper, the authors apply SAT based method to solve this problem. Two SAT solvers, walksat and zChaff, are employed to generate approximate and ...

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...

Given a formula of the propositional calculus, determining whether there exists a variable assignment such that the formula evaluates to true under the usual rules of interpretation is called the Boolean Satisfiability Problem, commonly abbreviated as SAT. SAT has a central role in the theory of computational complexity as it was the first computational task shown to be NP-complete. Subsequent ...

The SAT problem is maybe one of the most famous NP-complete problems. This paper deals with 3-SAT problem. We follow a sort incremental strategy to save computational costs respect classical quantum computing approach. present an heuristics that leads this strategy, improving performance purely random scheme. finally validate our approach by means thorough empirical study.

Rubik’s Cube is an easily-understood puzzle, which is originally called the “magic cube”. It is a well-known planning problem, which has been studied for a long time. Yet many simple properties remain unknown. This paper studies whether modern SAT solvers are applicable to this puzzle. To our best knowledge, we are the first to translate Rubik’s Cube to a SAT problem. To reduce the number of va...

Given a formula of the propositional calculus, determining whether there exists a variable assignment such that the formula evaluates to true under the usual rules of interpretation is called the Boolean Satisfiability Problem, commonly abbreviated as SAT. SAT has a central role in the theory of computational complexity as it was the first computational task shown to be NP-complete. Subsequent ...

The satisfiability problem (SAT) [6] consists in finding a truth assignment that satisfies a wellformed Boolean expression. An instance of the SAT problem is defined by a set of boolean variables (also called atoms) X = {x1, ..., xn} and a boolean formula φ: {0, 1}n → {0, 1}. A literal is a variable or its negation. A (truth) assignment is a function v:X → {0, 1}. The formula is said to be sati...

$EVWUDFW. In this paper we present a new approach to solve the satisfiability problem (SAT), based on boolean networks (BN). We define a mapping between a SAT instance and a BN, and we solve SAT problem by simulating the BN dynamics. We prove that BN fixed points correspond to the SAT solutions. The mapping presented allows to develop a new class of algorithms to solve SAT. Moreover, this new a...