An evolutionary framework for 3-SAT problems

Abstract

We present a new evolutionary framework for 3-SAT. This method can be divided into three stages, where each stage is an evolutionary algorithm. The first stage improves the quality of the initial population. The second stage improves the speed of the algorithm periodically generating new solutions. The third stage is a hybrid evolutionary algorithm, which improves the solutions with a local search. The key points of our algorithm are the evolutionary framework and the mutation operation that form a concatenated, complex neighborhood structure, "a variable neighborhood descent". We tested our algorithm on some benchmark problems. Comparing the results with other heuristic methods, we can conclude that our algorithm belongs to the best methods of this problem scope.