NSGA-III with crossover optimizes m-OJZJ asymptotically faster than without crossover for any m in large parameter regimes, with a matching lower bound for the four-objective case without crossover.
A mathematical runtime analysis of the non-dominated sorting genetic algorithm III (NSGA-III)
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On the Impact of Crossover in Many-Objective Optimization: A Runtime Analysis of NSGA-III
NSGA-III with crossover optimizes m-OJZJ asymptotically faster than without crossover for any m in large parameter regimes, with a matching lower bound for the four-objective case without crossover.