It seems the construction of SMS-EMOA is not correct in MGO.
Simple description of the algorithm say that :
The indicator-based EMOA use a quality indicator for the selection at least as a second stage measure. The SMS-EMOA follows this principle by first performing non-dominated sorting on the population and one offspring, and then for the worst subset, the hypervolume is determined and the individual with the least contribution to the hypervolume is denoted as the worst one and is discarded.
More detail can be found on the p59 to p65 of Nicolas Beume dissertation of 2011 named "Hypervolume-based Metaheuristics for Multiobjective Optimization"
SMS-EMOA use Non Dominated Sorting, then for only for the last front, the hypervolume ranking.
Actually, the non dominated sorting implemented in MGO is not used in the definition of SMS-EMOA .
trait SMSEMOEA <: Evolution
with GAGenomeWithSigma
with MG
with BinaryTournamentSelection
with TournamentOnRank
with HypervolumeRanking
with RankElitism
with DynamicGACrossover
with DynamicGAMutation
with FitnessHypervolumeDiversity
with NoArchive
with GeneticBreeding
with ClampedGenome
It seems the construction of SMS-EMOA is not correct in MGO.
Simple description of the algorithm say that :
More detail can be found on the p59 to p65 of Nicolas Beume dissertation of 2011 named "Hypervolume-based Metaheuristics for Multiobjective Optimization"
SMS-EMOA use Non Dominated Sorting, then for only for the last front, the hypervolume ranking.
Actually, the non dominated sorting implemented in MGO is not used in the definition of SMS-EMOA .