Abstract
When the traditional genetic algorithm was used to solve the community detection problem, it was not easy to avoid the problems of low efficiency and slow convergent speed. To be aim at these problems, a improved genetic algorithm which is based on the immune mechanism was proposed in this paper. In this new algorithm, the immune mechanism was used to ensure the diversity of population. Meanwhile, a improved character encoding was adopted to further reduce the search space. The results shows that the shortcomings of slow convergent speed and low efficiency could be overcome by using the improved genetic algorithm to solve these problems, compared with the traditional genetic algorithm.
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Acknowledgment
This work is supported by the National Natural Science Foundation of China with the Grant No. 61573157, the Fund of Natural Science Foundation of Guangdong Province of China with the Grant No. 2014A030313454.
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Li, K., Xiong, L. (2016). Community Detection Based on an Improved Genetic Algorithm. In: Li, K., Li, J., Liu, Y., Castiglione, A. (eds) Computational Intelligence and Intelligent Systems. ISICA 2015. Communications in Computer and Information Science, vol 575. Springer, Singapore. https://doi.org/10.1007/978-981-10-0356-1_4
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DOI: https://doi.org/10.1007/978-981-10-0356-1_4
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