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Although Path-Relinking is an effective local search method for manycombinatorial optimization problems, its application is not straightforward insolving the MAX-SAT, an optimization variant of the satisfiability problem(SAT) that has many real-world applications and has gained more and moreattention in academy and industry. Indeed, it was not used in any recentcompetitive MAX-SAT algorithms in our knowledge. In this paper, we propose anew local search algorithm called IPBMR for the MAX-SAT, that remedies thedrawbacks of the Path-Relinking method by using a careful combination of threecomponents: a new strategy named Path-Breaking to avoid unpromising regions ofthe search space when generating trajectories between two elite solutions; aweak and a strong mutation strategies, together with restarts, to diversify thesearch; and stochastic path generating steps to avoid premature local optimumsolutions. We then present experimental results to show that IPBMR outperformstwo of the best state-of-the-art MAX-SAT solvers, and an empiricalinvestigation to identify and explain the effect of the three components inIPBMR.

An Iterative Path-Breaking Approach with Mutation and Restart Strategies for the MAX-SAT Problem