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Evolutionary algorithms have emerged in the last twenty years as a powerful approach for dealing with multi-objective optimization problems (MOPs). Although classical multi-objective evolutionary algorithms (MOEAs), such as SPEA2 and NSGA-II, have been designed to manipulate any number of objectives, the results of their practical application to MOPs with more than three objectives revealed that they...