Abstract
In this paper, we postulate some desired behaviors of any evolutionary algorithm (EA) to demonstrate self-adaptive properties. Thereafter, by calculating population mean and variance growth equations, we find bounds on parameter values in a number of EA operators which will qualify them to demonstrate the self-adaptive behavior. Further, we show that if the population growth rates of different EAs are similar, similar performance is expected. This allows us to connect different self-adaptive EAs on an identical platform. This may lead us to find a more unified understanding of the working of different EAs.
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Beyer, HG., Deb, K. (2000). On the Desired Behaviors of Self-Adaptive Evolutionary Algorithms. In: Schoenauer, M., et al. Parallel Problem Solving from Nature PPSN VI. PPSN 2000. Lecture Notes in Computer Science, vol 1917. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45356-3_6
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DOI: https://doi.org/10.1007/3-540-45356-3_6
Publisher Name: Springer, Berlin, Heidelberg
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