Abstract
Binary ant colony algorithm has good performance in the function optimization problem. However, the drawbacks that easy to fall into the local optimization stll exist. Through the analysis of "best-so-far" pheromone update rule, we get the lower probability bound under this update rule. Then binary ant colony algorithm with Balanced search bias is proposed. Experiment results have shown that the improved algorithm has good globe search ability and need small iterate times. © 2010 IEEE.
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Hu, G., Xiong, W., Jiang, B., Yuan, J., & Zhang, X. (2010). Binary ant colony algorithm with balanced search bias. In Proceedings of the World Congress on Intelligent Control and Automation (WCICA) (pp. 3120–3125). https://doi.org/10.1109/WCICA.2010.5554964
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