Abstract
Heuristic optimisation techniques, especially evolutionary algorithms were successfully applied to non-stationary optimisation tasks. One of the most important conclusions for the evolutionary approach was a three-population architecture of the algorithm, where one population plays the role of a memory while the two others are used in the searching process. In this paper the authors’ version of the three-population architecture is applied to four different heuristic algorithms. One of the algorithms is a new iterated heuristic algorithm inspired by artificial immune system and proposed by the authors. The results of experiments with a non-stationary environment showing different properties of the algorithms are presented and some general conclusions are sketched.
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Trojanowski, K., Wierzchoń, S.T. (2003). Studying Properties of Multipopulation Heuristic Approach to 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 22. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-36562-4_3
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DOI: https://doi.org/10.1007/978-3-540-36562-4_3
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