Applies non-dominated sorting of the objective vectors and subsequent crowding distance computation to select a subset of individuals. This is the selector used by the famous NSGA-II EMOA (see nsga2).
selNondom(fitness, n.select)
Arguments
fitness: [matrix]
Matrix of fitness values (each column contains the fitness value(s) of one individual).
n.select: [integer(1)]
Number of elements to select.
Returns
[setOfIndividuals]
See Also
Other selectors: selDomHV(), selGreedy(), selRanking(), selRoulette(), selSimple(), selTournament()