By integrating artificial bee colony and genetic algorithm, a novel hybrid swarm intelligent approach is proposed in this paper. The main idea of the approach is to obtain the parallel computation merit of GA and the speed and self-improvement merits of ABC by sharing information between GA population and bee colony. To exam the proposed method, it is applied to 4 benchmark functions for different dimensions. For comparison, simple GA and ABC methods are also executed. Numerical results show that the proposed hybrid swarm intelligent method is effective, and the precision could be improved. © 2010 Springer-Verlag.
CITATION STYLE
Zhao, H., Pei, Z., Jiang, J., Guan, R., Wang, C., & Shi, X. (2010). A hybrid swarm intelligent method based on genetic algorithm and artificial bee colony. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6145 LNCS, pp. 558–565). https://doi.org/10.1007/978-3-642-13495-1_68
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