Abstract
This paper reports on novel work using clonal selection (CS) for dynamic function optimisation. A comparison is made between evolution strategies (ES) and CS, for the optimisation of two significantly different dynamic functions at 2, 5 and 10 dimensions. Firstly a sensitivity analysis was performed for both the CS and the ES for both fitness functions. Secondly the performance of the two algorithms was compared over time. The main finding of this work is that the CS optimises better than the ES in problems with few dimensions, although the ES optimises more slowly. At higher dimensions however, the ES optimises both more quickly and to a better level.
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Walker, J.H., Garrett, S.M. (2003). Dynamic Function Optimisation: Comparing the Performance of Clonal Selection and Evolution Strategies. In: Timmis, J., Bentley, P.J., Hart, E. (eds) Artificial Immune Systems. ICARIS 2003. Lecture Notes in Computer Science, vol 2787. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45192-1_26
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DOI: https://doi.org/10.1007/978-3-540-45192-1_26
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