Based on Lamarckism and Immune Clonal Selection Theory, Lamarckian Clonal Selection Algorithm (LCSA) is proposed in this paper. In the novel algorithm, the idea that Lamarckian evolution described how organism can evolve through learning, namely the point of "Gain and Convey" is applied, then this kind of learning mechanism is introduced into Standard Clonal Selection Algorithm (SCSA). Through the experimental results of optimizing complex multimodal functions, compared with SCSA and the relevant evolutionary algorithm, LCSA is more robust and has better convergence. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
He, W., Du, H., Jiao, L., & Li, J. (2005). Lamarckian Clonal Selection Algorithm based function optimization. In Lecture Notes in Computer Science (Vol. 3512, pp. 91–98). Springer Verlag. https://doi.org/10.1007/11494669_12
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