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GRASP: A Novel Search Algorithm for Propositional Satisfiability (SAT)

GRASP (Generic Reasoning with Algorithms and Satisfiability Procedures) is a cutting-edge search algorithm designed to solve propositional satisfiability (SAT) problems efficiently. By finding a variable assignment that makes a Boolean formula evaluate to true or proving that no such assignment exists, GRASP addresses NP-complete challenges. Utilizing conflict-driven learning and non-chronological backtracking, GRASP significantly enhances search efficiency compared to traditional methods. This algorithm is foundational for modern SAT solvers and demonstrates practical capabilities in solving complex SAT instances.

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GRASP: A Novel Search Algorithm for Propositional Satisfiability (SAT)

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  1. GRASP: A Search Algorithm for Propositional Satisfiability

  2. Sat in a Nutshell • Given a Boolean formula, find a variable assignment such that the formula evaluates to 1, or prove that no such assignment exists. • For n variable,s there are 2n possible truth assignments to be checked. • NP-Complete problem.

  3. Problem Representation • Conjunctive Normal Form • F = (a+b)(a’+b’+c) • Simple representation (more efficient data structures) • Logic circuit representation • Circuits have structural and direction information • Circuit –-> CNF conversion is straightforward

  4. DLL Algorithm

  5. DLL Algorithm • Davis, Logemann and Loveland • M. Davis, G. Logemann and D. Loveland, “A Machine Program for Theorem-Proving”, Communications of ACM, Vol. 5, No. 7, pp. 394-397, 1962 • Basic framework for many modern SAT solvers • Also known as DPLL for historical reasons • DFS – depth first search

  6. Implications and BooleanConstraint Propagation

  7. Implications and BooleanConstraint Propagation • Implication • A variable is forced to be assigned to be True or False based on previous assignments. • Unit clause rule (rule for elimination of one literal clauses) • An unsatisfied clause is a unit clause if it has exactly one unassigned literal. • The unassigned literal is implied because of the unit clause. • Boolean Constraint Propagation (BCP) • Iteratively apply the unit clause rule until there is no unit clause available • Workhorse of DLL based algorithms.

  8. GRASP • Marques-Silva and Sakallah [SS96,SS99] • J.P.Marques-Silva and K.A.Sakallah,”GRASP – A New Search Algorithm for Satisfiability,” Proc. ICCAD 1996. (49 citations) • Incorporates conflict driven learning and non-chronological backtracking • Practical SAT instances can be solved in reasonable time • Bayardo and Schrag’s RelSAT also proposed conflict driven learning [BS97]

  9. Conflict Driven Learning and Non-Chronological Backtracking

  10. Conflict Clause • Significantly prune the search speace • Learned clause is useful forever • Useful in generating future conflict clauses

  11. GRASP: A Search Algorithm for Propositional Satisfiability EE878C Homework #2 2002/11/1 KAIST, EECS ICS Lab Lee, Dongsoo

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