Abstract
Mammalian immune system and especially clonal selection principle, responsible for coping with external intruders, is an inspiration for a set of heuristic optimization algorithms. Below, a few of them are compared on a set of nonstationary optimization benchmarks. One of the algorithms is our proposal, called AIIA (Artificial Immune Iterated Algorithm). We compare two versions of this algorithm with two other well known algorithms. The results show that all the algorithms based on clonal selection principle can be quite efficient tools for nonstationary optimization.
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Trojanowski, K., Wierzchoń, S.T. (2006). A Comparison of Clonal Selection Based Algorithms for Non-Stationary Optimisation Tasks. In: Kłopotek, M.A., Wierzchoń, S.T., Trojanowski, K. (eds) Intelligent Information Processing and Web Mining. Advances in Soft Computing, vol 35. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-33521-8_5
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DOI: https://doi.org/10.1007/3-540-33521-8_5
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