Abstract
In this paper, a variable-neighbourhood-genetic-based-algorithm is proposed for the MAX-SAT problem. Most of the work published earlier on variable neighbourhood search VNS starts from the first neighbourhood and moves on to higher neighbourhoods without controlling and adapting the ordering of neighbourhood structures. The order in which the neighbourhood structures have been proposed during the search process in this work enables the genetic algorithm with a better mechanism for performing diversification and intensification. A set of benchmark problem instances is used to compare the effectiveness of the proposed algorithm against the standard genetic algorithm. We also report promising results when the proposed algorithm is compared with state-of-the-art solvers.
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