Abstract
The minimum positive influence dominating set problem is one of the central problems in the study of online social networks. This paper presents a hybrid swarm intelligence-based algorithm to solve the minimum positive influence dominating set problem. The proposed swarm intelligence-based algorithm is based on genetic algorithm and particle swarm optimization. Firstly, a greedy randomized adaptive construction procedure is employed to generate initial swarm. Secondly, a crossover procedure is applied to obtain new solutions. Then, a mutation procedure is introduced to diversify the population. Finally, a repair procedure is used to ensure the feasibility of new solutions. Nine social networks from the literature are applied to test the proposed algorithm. The experimental results show that the proposed algorithm can achieve significant improvements over the existing greedy algorithms.
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Lin, G., Luo, J., Xu, H., Xu, M. (2020). A Hybrid Swarm Intelligence-Based Algorithm for Finding Minimum Positive Influence Dominating Sets. In: Liu, Y., Wang, L., Zhao, L., Yu, Z. (eds) Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery. ICNC-FSKD 2019. Advances in Intelligent Systems and Computing, vol 1074. Springer, Cham. https://doi.org/10.1007/978-3-030-32456-8_55
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DOI: https://doi.org/10.1007/978-3-030-32456-8_55
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