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- W2014747921 abstract "Inspired by the fact that the division of labor and cooperation play extremely important roles in the human history development, this paper develops a novel artificial bee colony algorithm based on information learning (ILABC, for short). In ILABC, at each generation, the whole population is divided into several subpopulations by the clustering partition and the size of subpopulation is dynamically adjusted based on the last search experience, which results in a clear division of labor. Furthermore, the two search mechanisms are designed to facilitate the exchange of information in each subpopulation and between different subpopulations, respectively, which acts as the cooperation. Finally, the comparison results on a number of benchmark functions demonstrate that the proposed method performs competitively and effectively when compared to the selected state-of-the-art algorithms." @default.
- W2014747921 created "2016-06-24" @default.
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- W2014747921 date "2015-12-01" @default.
- W2014747921 modified "2023-10-14" @default.
- W2014747921 title "Artificial Bee Colony Algorithm Based on Information Learning" @default.
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- W2014747921 doi "https://doi.org/10.1109/tcyb.2014.2387067" @default.
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