ON THE EFFECTIVENESS OF CROSSOVER IN SIMULATED EVOLUTIONARY OPTIMIZATION

There has been renewed interest in using simulated evolution to addres s difficult optimization problems. These simulations can be divided in to two groups: (1) those that model chromosomes and emphasize genetic operators; and (2) those that model individuals or populations and emp hasize the adaptation and diversity of behavior. Recent claims have su ggested that genetic models using recombination operators, specificall y crossover, are typically more efficient and effective at function op timization than behavioral models that rely solely on mutation. These claims are assessed empirically on a broad range of response surfaces.