Abstract
Measuring fitness progression using numeric quantification in an Evolutionary Computation (EC) system may not be sufficient to capture the rate of evolution precisely. In this paper, we define the rate of evolution \(R_{\mathrm e}\) in an EC system based on the rate of efficient genetic variations being accepted by the EC population. This definition is motivated by the measurement of “amino acid to synonymous substitution ratio” \(k_{\mathrm a}/k_{\mathrm s}\) in biology, which has been widely accepted to measure the rate of gene sequence evolution. Experimental applications to investigate the effects of four major configuration parameters on our rate of evolution measurement show that \(R_{\mathrm e}\) well reflects how evolution proceeds underneath fitness development and provides some insights into the effectiveness of EC parameters in evolution acceleration.
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Hu, T., Banzhaf, W. (2008). Nonsynonymous to Synonymous Substitution Ratio \(k_{\mathrm a}/k_{\mathrm s}\): Measurement for Rate of Evolution in Evolutionary Computation. In: Rudolph, G., Jansen, T., Beume, N., Lucas, S., Poloni, C. (eds) Parallel Problem Solving from Nature – PPSN X. PPSN 2008. Lecture Notes in Computer Science, vol 5199. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87700-4_45
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DOI: https://doi.org/10.1007/978-3-540-87700-4_45
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