Niching Prospects
نویسنده
چکیده
Although a large number of evolutionary algorithms have been proposed to efficiently treat multimodal problems, it is currently unclear under what conditions they can be faster than iterated local search algorithms. We tackle this question, assuming we had means to efficiently and errorlessly determine the corresponding basin of attraction for each individual (basin identification) by employing a simplified niching model EA that avoids superfluous local searches. Monte Carlo simulations show that outperforming the iterated local search is possible but difficult; the expected speedup is rather low if basins are approximately equally sized.
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