A multiobjective genetic algorithm based on NSGA II for deriving final ranking from a medium-sized fuzzy outranking relation

In this paper, a heuristic, based on the non dominated sorting genetic algorithm II (NSGA II), is developed to exploit a known fuzzy outranking relation, with the purpose of constructing a recommendation for a medium-sized multicriteria ranking problem. The performance of the proposed evolutionary algorithm is evaluated on a real medium-sized problem. The results indicate that the proposed evolutionary algorithm can effectively be used to solve medium-sized multicriteria ranking problems.