Using SAT Encodings to Derive CSP Value Ordering Heuristics
Author(s) -
Christophe Lecoutre,
Lakhdar Saïs,
Julien Vion
Publication year - 2007
Publication title -
journal on satisfiability boolean modeling and computation
Language(s) - English
Resource type - Journals
eISSN - 1875-5011
pISSN - 1574-0617
DOI - 10.3233/sat190010
Subject(s) - heuristics , backtracking , exploit , computer science , heuristic , constraint satisfaction problem , variable (mathematics) , reduction (mathematics) , constraint (computer aided design) , context (archaeology) , mathematical optimization , theoretical computer science , algorithm , mathematics , artificial intelligence , mathematical analysis , paleontology , geometry , computer security , probabilistic logic , biology
In this paper, we address the issue of designing from SAT new value ordering heuristics for CSP. We show that using the direct and support SAT encodings of CSP instances, such heuristics can be naturally derived from the well-known two-sided Jeroslow-Wang heuristic. These heuristics exploit the bi-directionality of constraint supports to give a more comprehensive picture in terms of domain reduction when a given value is assigned to (resp. removed from) a given variable. Interestingly, in the context of a backtracking search algorithm that exploits binary branching and the adaptive variable ordering heuristic dom=wdeg, we experimentally observed that the new heuristics yielded the best results on satisable and unsatisable instances when following the promise and the fail-first policies, respectively.
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