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Evolved preambles for MAX-SAT heuristics

By Luis O. Rigo Jr and Valmir C. Barbosa


MAX-SAT heuristics normally operate from random initial truth assignments to the variables. We consider the use of what we call preambles, which are sequences of variables with corresponding single-variable assignment actions intended to be used to determine a more suitable initial truth assignment for a given problem instance and a given heuristic. For a number of well established MAX-SAT heuristics and benchmark instances, we demonstrate that preambles can be evolved by a genetic algorithm such that the heuristics are outperformed in a significant fraction of the cases

Topics: Computer Science - Artificial Intelligence, Computer Science - Neural and Evolutionary Computing
Year: 2011
DOI identifier: 10.5220/0003660400230031
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