Propagation = lazy clause generation

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Propagation = lazy clause generation (2007)

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by Olga Ohrimenko , Peter J. Stuckey , Michael Codish

Venue:	Proceedings of the 13th International Conference on Principles and Practice of Constraint Programming, LNCS
Citations:	22 - 12 self

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@INPROCEEDINGS{Ohrimenko07propagation=,
    author = {Olga Ohrimenko and Peter J. Stuckey and Michael Codish},
    title = {Propagation = lazy clause generation},
    booktitle = {Proceedings of the 13th International Conference on Principles and Practice of Constraint Programming, LNCS},
    year = {2007},
    publisher = {Springer-Verlag}
}

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Abstract

Abstract. Finite domain propagation solvers effectively represent the possible values of variables by a set of choices which can be naturally modelled as Boolean variables. In this paper we describe how we can mimic a finite domain propagation engine, by mapping propagators into clauses in a SAT solver. This immediately results in strong nogoods for finite domain propagation. But a naive static translation is impractical except in limited cases. We show how we can convert propagators to lazy clause generators for a SAT solver. The resulting system can solve scheduling problems significantly faster than generating the clauses from scratch, or using Satisfiability Modulo Theories solvers with difference logic. 1

Keyphrases

propagation lazy clause generation sat solver finite domain propagation engine boolean variable possible value finite domain propagation naive static translation limited case difference logic satisfiability modulo theory solver finite domain propagation solver clause generator strong nogoods

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