11 March 2002 Results on a fractal measure for evolutionary optimization
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Evolutionary optimizers employ independent Gaussian random variables as a central component for their processing, which often renders them immune to analysis. This paper investigates the applicability of the Hurst dimension, a fractal dimension, as a characterization of processing in an evolutionary optimizer. Results show that this fractal measure does highlight some interesting processing commonalities between standard and self-adaptive evolutionary optimization. A potentially worthwhile modification to evolutionary optimization is suggested based on the results.
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Peter J. Angeline, "Results on a fractal measure for evolutionary optimization", Proc. SPIE 4739, Applications and Science of Computational Intelligence V, (11 March 2002); doi: 10.1117/12.458701; https://doi.org/10.1117/12.458701

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