For four or more objectives, the NSGA-II with population size linear in the Pareto front misses a constant fraction of the Pareto front of LOTZ for exponentially long time.
Near-tight runtime guar- antees for many-objective evolutionary algorithms
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.NE 1years
2024 1verdicts
ACCEPT 1representative citing papers
citing papers explorer
-
Difficulties of the NSGA-II with the Many-Objective LeadingOnes Problem
For four or more objectives, the NSGA-II with population size linear in the Pareto front misses a constant fraction of the Pareto front of LOTZ for exponentially long time.