Abstract
In present time some researchers use chaotic numbers generators in evolutionary algorithms like differential evolution, SOMA or particle swarm optimization. These chaotic numbers generators are based on chaotic discrete systems which replace pseudorandom numbers generators like Mersenne Twister, Xorshift etc. In this paper we will investigate the influence of chaos level in logistic map which is used as chaotic numbers generator to the convergence’s speed of differential evolution to the global minimum of testing functions.
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Skanderova, L., Zelinka, I., Dao, T.T., Hoang, D.V. (2014). Chaos Level Measurement in Logistic Map Used as the Chaotic Numbers Generator in Differential Evolution. In: Zelinka, I., Suganthan, P., Chen, G., Snasel, V., Abraham, A., Rössler, O. (eds) Nostradamus 2014: Prediction, Modeling and Analysis of Complex Systems. Advances in Intelligent Systems and Computing, vol 289. Springer, Cham. https://doi.org/10.1007/978-3-319-07401-6_1
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DOI: https://doi.org/10.1007/978-3-319-07401-6_1
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07400-9
Online ISBN: 978-3-319-07401-6
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