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Enhancing the Robustness/Efficiency of Local Search Algorithms for SAT

Walksat-like algorithms are considered among the most powerful local search methods to solve the satisfiability problem. Such algorithms introduce a diversification mechanism based on a random walk strategy. This one is controlled by a noise parameter for which the optimal value setting is strongly dependent on the treated instance. In this paper, we propose to extend a previous work in order to reduce the sensitivity of such algorithms to this setting. This task is accomplished by taking into account relations between variables and a cooperation with a DPLL-like procedure.