In this paper we investigate the use of quantum particle swarm optimization (QPSO) principles to resolve the satisfiability problem. We describe QPSOSAT, a new iterative approach for solving the well known Maximum Satisfiability (MAX-SAT) problem. This latter has been shown to be NP-hard if the number of variables per clause is greater than 3. The underlying idea is to harness the optimization capabilities of QPSO algorithm to achieve good quality solutions for Max Sat problem. To foster the process, a local search has been used. The obtained results are very encouraging and show the feasibility and effectiveness of the proposed hybrid approach.
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