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.
Crossover can provably be useful in evolution- ary computation.Theoretical Computer Science, 425:17– 33
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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.