In order to optimize the performance of the transmission network (TN), this paper introduces the random fractal search algorithm based on the beetle antenna search algorithm, thus proposing the random fractal beetle antenna algorithm (SFBA). The main work of this research is as follows: (1) in the beetle antenna search algorithm, this study used a population of beetles and introduced elite members of the population in order to make the algorithm more stable and to some extent improve the accuracy of its answers. (2) Utilizing the elite reverse learning method and the leader’s multilearning strategy for elites helps to strike a balance between the global exploration and local development of the algorithm. This strategy also further improves the ability of the algorithm to find the optimal solution. (3) Experiments on real experimental data show that the SFBA algorithm proposed in this paper is effective in improving TN performance. In summary, the research content of this paper provides a good reference value for the performance optimization of TN in actual production.
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