MiniMaxSat: A New Weighted Max-SAT Solver

Heras, Federico; Larrosa, Javier; Oliveras, Albert

doi:10.1007/978-3-540-72788-0_8

Cited by 53 publications

(83 citation statements)

References 23 publications

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“…The first approach is to perform Branch and Bound search where a lower bound is computed by exploiting the logical structure of the CNF input, e.g., [9,14]. The second approach is to solve the maxsat problem as a sequence of sat problems.…”

Section: Existing Maxsat Solversmentioning

confidence: 99%

“…We performed an empirical study of nine existing maxsat solvers: cplex (version 12.2), wpm1 (with the latest 2012 improvements [1]), wpm2 (version 2 [2]), bincd [10], wbo [15], minimaxsat [9], sat4j [4], akmaxsat [13], and maxhsOrig [7]. All of these solvers are able to solve maxsat in its most general form, i.e., weighted partial maxsat, and thus have the widest range of applicability.…”

Section: Empirical Evaluation Of Current Maxsat Solversmentioning

confidence: 99%

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Exploiting the Power of mip Solvers in maxsat

Davies

Bacchus

2013

Theory and Applications of Satisfiability Testing – SAT 2013

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Abstract. maxsat is an optimization version of satisfiability. Since many practical problems involve optimization, there are a wide range of potential applications for effective maxsat solvers. In this paper we present an extensive empirical evaluation of a number of maxsat solvers. In addition to traditional maxsat solvers, we also evaluate the use of a state-of-the-art Mixed Integer Program (mip) solver, cplex, for solving maxsat. mip solvers are the most popular technology for solving optimization problems and are also theoretically more powerful than sat solvers. In fact, we show that cplex is quite effective on a range of maxsat instances. Based on these observations we extend a previously developed hybrid approach for solving maxsat, that utilizes both a sat solver and a mip solver. Our extensions aim to take better advantage of the power of the mip solver. The resulting improved hybrid solver is shown to be quite effective.

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Section: Existing Maxsat Solversmentioning

confidence: 99%

Section: Empirical Evaluation Of Current Maxsat Solversmentioning

confidence: 99%

Exploiting the Power of mip Solvers in maxsat

Davies

Bacchus

2013

Theory and Applications of Satisfiability Testing – SAT 2013

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“…Current most effective complete MaxSAT solvers are either based on branch and bound or on iteratively calling a SAT oracle. MiniMaxSat (MM) [9] was selected among other branch and bound solvers, because it takes additional advantage of clause learning and backjumping on the instances considered. 3 solvers based on calling a SAT oracle were considered.…”

Section: Experimental Evaluationmentioning

confidence: 99%

“…For this reason, this paper does not consider hard groups. Early MaxSAT solvers, predecessors to modern branch and bound [9] and coreguided MaxSAT solvers [2], are compared in [4] against the native solver by translating the Group MaxSAT problem into MaxSAT using a primitive version of the double weight encoding. Nevertheless, experiments on similar benchmarks (MaxCSP and QCP) indicate that modern MaxSAT solvers with the appropriate encoding are orders of magnitude faster than the native solver in [4].…”

Section: Related Workmentioning

confidence: 99%

An Empirical Study of Encodings for Group MaxSAT

Heras

Morgado

Marques-Silva

2012

Advances in Artificial Intelligence

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Abstract. Weighted Partial MaxSAT (WPMS) is a well-known optimization variant of Boolean Satisfiability (SAT) that finds a wide range of practical applications.WPMS divides the formula in two sets of clauses: The hard clauses that must be satisfied and the soft clauses that can be unsatisfied with a penalty given by their associated weight. However, some applications may require each constraint to be modeled as a set or group of clauses. The resulting formalism is referred to as Group MaxSAT. This paper overviews Group MaxSAT, and shows how several optimization problems can be modeled as Group MaxSAT. Several encodings from Group MaxSAT to standard MaxSAT are formalized and refined. A comprehensive empirical study compares the performance of several MaxSAT solvers with the proposed encodings. The results indicate that, depending on the underlying MaxSAT solver and problem domain, the solver may perform better with a given encoding than with the others.

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“…The first approach is to utilize the logical structure of the CNF input to enable the computation of lower-bounds during a branch and bound search, e.g., [7,11]. The second approach is to reduce the problem to solving a sequence of SAT problems.…”

Section: Introductionmentioning

confidence: 99%

Solving MAXSAT by Solving a Sequence of Simpler SAT Instances

Davies

Bacchus

2011

Lecture Notes in Computer Science

101

103

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Abstract.Maxsat is an optimization version of Satisfiability aimed at finding a truth assignment that maximizes the satisfaction of the theory. The technique of solving a sequence of SAT decision problems has been quite successful for solving larger, more industrially focused Maxsat instances, particularly when only a small number of clauses need to be falsified. The SAT decision problems, however, become more and more complicated as the minimal number of clauses that must be falsified increases. This can significantly degrade the performance of the approach. This technique also has more difficulty with the important generalization where each clause is given a weight: the weights generate SAT decision problems that are harder for SAT solvers to solve. In this paper we introduce a new Maxsat algorithm that avoids these problems. Our algorithm also solves a sequence of SAT instances. However, these SAT instances are always simplifications of the initial Maxsat formula, and thus are relatively easy for modern SAT solvers. This is accomplished by moving all of the arithmetic reasoning into a separate hitting set problem which can then be solved with techniques better suited to numeric reasoning, e.g., techniques from mathematical programming. As a result the performance of our algorithm is unaffected by the addition of clause weights. Our algorithm can, however, require solving more SAT instances than previous approaches. Nevertheless, the approach is simpler than previous methods and displays superior performance on some benchmarks.

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MiniMaxSat: A New Weighted Max-SAT Solver

Cited by 53 publications

References 23 publications

Exploiting the Power of mip Solvers in maxsat

Exploiting the Power of mip Solvers in maxsat

An Empirical Study of Encodings for Group MaxSAT

Solving MAXSAT by Solving a Sequence of Simpler SAT Instances

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