Efficient conflict driven learning in a boolean satisfiability solver
Lintao Zhang,Conor F. Madigan,Matthew H. Moskewicz,Sharad Malik +3 more
- pp 279-285
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This paper generalizes various conflict driven learning strategies in terms of different partitioning schemes of the implication graph to re-examine the learning techniques used in various SAT solvers and propose an array of new learning schemes.Abstract:
One of the most important features of current state-of-the-art SAT solvers is the use of conflict based backtracking and learning techniques. In this paper, we generalize various conflict driven learning strategies in terms of different partitioning schemes of the implication graph. We re-examine the learning techniques used in various SAT solvers and propose an array of new learning schemes. Extensive experiments with real world examples show that the best performing new learning scheme has at least a 2/spl times/ speedup compared with learning schemes employed in state-of-the-art SAT solvers.read more
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Book ChapterDOI
An Extensible SAT-solver
Niklas Een,Niklas Sörensson +1 more
TL;DR: This article presents a small, complete, and efficient SAT-solver in the style of conflict-driven learning, as exemplified by Chaff, and includes among other things a mechanism for adding arbitrary boolean constraints.
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Handbook of Constraint Programming
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SATzilla: portfolio-based algorithm selection for SAT
TL;DR: SATzilla is described, an automated approach for constructing per-instance algorithm portfolios for SAT that use so-called empirical hardness models to choose among their constituent solvers and is improved by integrating local search solvers as candidate solvers, by predicting performance score instead of runtime, and by using hierarchical hardness models that take into account different types of SAT instances.
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Solving SAT and SAT Modulo Theories: From an abstract Davis--Putnam--Logemann--Loveland procedure to DPLL(T)
TL;DR: Extensive experimental evidence shows that DPLL(T) systems can significantly outperform the other state-of-the-art tools, frequently even in orders of magnitude, and have better scaling properties.
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Satisfiability Modulo Theories
Clark Barrett,Cesare Tinelli +1 more
TL;DR: The architecture of a lazy SMT solver is discussed, examples of theory solvers are given, how to combine such solvers modularly is shown, and several extensions of the lazy approach are mentioned.
References
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Proceedings Article
Local Search with Constraint Propagation and Conflict-Based Heuristics
Narendra Jussien,Olivier Lhomme +1 more
TL;DR: This paper presents a new hybrid technique that performs a local search over partial assignments instead of complete assignments, and uses filtering techniques and conflict-based techniques to efficiently guide the search.
Journal ArticleDOI
Job Shop Scheduling by Local Search
TL;DR: In this paper, a survey of local search methods for the job shop scheduling problem is presented, with an emphasis on local search, both deterministic and randomized local search and the proposed neighborhoods are discussed.
Journal Article
The impact of branching heuristics in propositional satisfiability algorithms
TL;DR: Empirical evidence is provided that for practical instances of SAT, the search pruning techniques included in the most competitive SAT algorithms may be of more fundamental significance than branching heuristics.
Proceedings Article
Automatic SAT-compilation of planning problems
TL;DR: A fully-implemented compiler is described that can generate eight major encodings and a number of subsidiary ones, and the compiler is tested on a suite of STRIPS planning problems in order to determine whichencodings have the best properties.