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The satisfiability problem (SAT) is a typical NP-complete problem where a wide range of applications has been studied. Given a set of variables U and a set of clauses C, the goal of SAT is to find a truth assignment to variables in U such that every clause in C is satisfied if it exits, or to derive the infeasibility otherwise. This paper presents an approximation algorithm, called a minimal-state processing search algorithm for SAT (MIPS-SAT). MIPS-SAT repeatedly transits minimal states in terms of the cost function for searching a solution through a construction stage and a refinement stage. The first stage greedily generates an initial state composed of as many satisfied clauses as possible. The second stage iteratively seeks a solution while keeping state minimality. The performance of MIPS-SAT is verified through solving DIMACS benchmark instances
Digital Object Identifier: 10.1109/ICSMC.2001.972986
Published with permission from the copyright holder. This is the institute's copy, as published in Systems, Man, and Cybernetics, 2001 IEEE International Conference on, 7-10 Oct. 2001, Vol. 4, Pages 2769-2774.
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