Abstract
The influence of different parallel genetic algorithm (PGA) architectures on the GA convergence properties is analysed. Next, two proposed versions of these PGA architectures are compared – homogenous and heterogeneous. Finally the effect of re-initialisation in some partial populations on the PGA convergence has been analysed. The proposed PGA modifications are useful mainly in case of non-smooth cost function optimisation.
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© 2004 Springer-Verlag Berlin Heidelberg
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Sekaj, I. (2004). Robust Parallel Genetic Algorithms with Re-initialisation. In: Yao, X., et al. Parallel Problem Solving from Nature - PPSN VIII. PPSN 2004. Lecture Notes in Computer Science, vol 3242. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30217-9_42
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DOI: https://doi.org/10.1007/978-3-540-30217-9_42
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23092-2
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