2001 | OriginalPaper | Buchkapitel
Evaluating Search Heuristics and Optimization Techniques in Propositional Satisfiability
verfasst von : Enrico Giunchiglia, Massimo Maratea, Armando Tacchella, Davide Zambonin
Erschienen in: Automated Reasoning
Verlag: Springer Berlin Heidelberg
Enthalten in: Professional Book Archive
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
This paper is devoted to the experimental evaluation of several state-of-the-art search heuristics and optimization techniques in propositional satisFIability (SAT). The test set consists of random 3CNF formulas as well as real world instances from planning, scheduling, circuit analysis, bounded model checking, and security protocols. All the heuristics and techniques have been implemented in a new library for SAT, called SIM. The comparison is fair because in sim the selected heuristics and techniques are realized on a common platform. The comparison is significative because sim as a solver performs very well when compared to other state- of-the-art solvers.