background and objective: magnetic resonance imaging (mri) is the most sensitive technique to detect multiple sclerosis (ms) plaques in central nervous system. in some cases, the patients who were suspected to ms, whereas mri images are normal, but whether patients don’t have ms plaques or mri images are not enough optimized enough in order to show ms plaques? the aim of the current study is ev...

Certifying a SAT solver for unsatisfiable instances is a computationally hard problem. Nevertheless, in the utilization of SAT in industrial settings, one often needs to be able to generate unsatisfiability proofs, either to guarantee the correctness of the SAT solver or as part of the utilization of SAT in some applications (e.g. in model checking). As part of the process of generating unsatis...

Current algorithms for bounded model checking (BMC) use SAT methods for checking satisfiability of Boolean formulas. These BMC methods suffer from a potential memory explosion problem. Methods based on the validity of Quantified Boolean Formulas (QBF) allow an exponentially more succinct representation of the checked formulas, but have not been widely used, because of the lack of an efficient d...

Most symbolic model checkers are based on either Binary Decision Diagrams (BDDs), which may grow exponentially large, or Satisfiability (SAT) solvers, whose time requirements rapidly increase with the sequential depth of the circuit. We investigate the integration of BDD-based methods with SAT to speed up the verification of safety properties of the form G f , where f is either propositional or...

The marriage in honey–bees optimization (MBO) algorithm was recently proposed and showed good results for combinatorial optimization problems. Contrary to most of the swarm intelligence algorithms (such as Ant Colony Optimization), MBO uses self-organization to mix different heuristics. This paper presents a variation of the MBO algorithm where the colony contains a single queen with multiple w...

While it is known how to generate satisfiable instances by reducing certain computational problems to SAT, it is not known how a similar generator can be developed directly for k-SAT. In this work we almost answer this question affirmatively by improving upon previous results in many ways. First, we give a generator for instances of MAX k-SAT, the version of k-SAT where one wants to maximize th...

We perform a systematic comparison of SAT and CSP models for a challenging combinatorial problem, quasigroup completion (QCP). Our empirical results clearly indicate the superiority of the 3D SAT encoding (Kautz et al. 2001), with various solvers, over other SAT and CSP models. We propose a partial explanation of the observed performance. Analytically, we focus on the relative conciseness of th...

We consider the satisfiability phase transition in skewed random k-SAT distributions. It is known that the random k-SAT model, in which the instance is a set of m k-clauses selected uniformly from the set of all k-clauses over n variables, has a satisfiability phase transition at a certain clause density. The essential feature of the random k-SAT is that positive and negative literals occur wit...

We study an Achlioptas-process version of the random k-SAT process: a bounded number of k-clauses are drawn uniformly at random at each step, and exactly one added to the growing formula according to a particular rule. We prove the existence of a rule that shifts the satisfiability threshold. This extends a well-studied area of probabilistic combinatorics (Achlioptas processes) to random CSP’s....

We present Regular-SAT, an extension of Boolean Satisfiability based on a class of many-valued CNF formulas. Regular-SAT shares many properties with Boolean SAT, which allows us to generalize some of the best known SAT results and apply them to Regular-SAT. In addition, Regular-SAT has a number of advantages over Boolean SAT. Most importantly, it produces more compact encodings that capture pro...