A Hybrid Swarm Intelligence-Based Algorithm for Finding Minimum Positive Influence Dominating Sets

  • Geng LinEmail author
  • Jinyan Luo
  • Haiping Xu
  • Meiqin Xu
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1074)


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.


Minimum positive influence dominating set Swarm intelligence Heuristic Local search 


  1. 1.
    Zeng, Y., Chen, X., Cong, G., Qin, S., Tang, J., Xiang, Y.: Maximizing influence under influence constraint in social networks. Expert Syst. Appl. 55, 255–267 (2016)CrossRefGoogle Scholar
  2. 2.
    Zhang, W., Wu, W., Wang, F., Xu, K.: Positive influence dominating sets in power-law graphs. Soc. Netw. Anal. Min. 2, 31–37 (2012)CrossRefGoogle Scholar
  3. 3.
    Lin, G., Guan, J., Feng, H.: An ILP based memetic algorithm for finding minimum positive influence dominating sets in social networks. Phys. A 500, 199–209 (2018)MathSciNetCrossRefGoogle Scholar
  4. 4.
    Wang, F., Du, H., Camacho, E., Xu, K., Lee, W., Shi, Y., Shan, S.: On positive influence dominating set in social networks. Theor. Comput. Sci. 412, 265–269 (2011)MathSciNetCrossRefGoogle Scholar
  5. 5.
    Zhu, X., Yu, J., Lee, W., Kim, D., Shan, S., Du, D.Z.: New dominating sets in social networks. J. Global Optim. 48, 633–642 (2010)MathSciNetCrossRefGoogle Scholar
  6. 6.
    Ran, Y., Zhang, Z., Du, H., Zhu, Y.: Approximation algorithm for partial positive influence problem in social network. J. Comb. Optim. 33, 791–802 (2017)MathSciNetCrossRefGoogle Scholar
  7. 7.
    Dinh, T.N., Shen, Y., Nguyen, D.T., Thai, M.T.: On the approximability of positive influence dominating set in social networks. J. Comb. Optim. 27(3), 487–503 (2014)MathSciNetCrossRefGoogle Scholar
  8. 8.
    Khomami, M.M.D., Rezvanian, A., Bagherpour, N., Meybodi, M.R.: Minimum positive influence dominating set and its application in influence maximization: a learning automata approach. Appl. Intell. 48(3), 570–593 (2018)CrossRefGoogle Scholar
  9. 9.
    Wang, F., Camacho, E., Xu, K.: Positive influence dominating set in online social networks. In: Du, D.Z., Hu, X. (eds.) Combinatorial Optimization and Applications. Lecture Notes in Computer Science, vol. 5573, pp. 313–321. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  10. 10.
    Raei, H., Yazdani, N., Asadpour, M.: A new algorithm for positive influence dominating set in social network. In: Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining, pp. 253-257. IEEE Computer Society (2012)Google Scholar
  11. 11.
    Fei, M., Chen, D.: An improved algorithm for finding minimum positive influence dominating sets in social networks. J. South China Normal Univ. Nat. Sci. Ed. 48(3), 59–63 (2016)MathSciNetGoogle Scholar
  12. 12.
    Holland, J.H.: Adaptation in Natural and Artificial Systems. The University of Michigan Press, Ann Arbor (1975)Google Scholar
  13. 13.
    Liang, J., Xu, W., Yue, C., Yu, K., Song, H., Crisalle, O.D., Qu, B.: Multimoda multiobjective optimization with differential evolution. Swarm Evol. Comput. 44, 1028–1059 (2019)CrossRefGoogle Scholar
  14. 14.
    Lin, G., Guan, J.: A hybrid binary particle swarm optimization for the obnoxious p-median problem. Inf. Sci. 425, 1–17 (2018)MathSciNetCrossRefGoogle Scholar
  15. 15.
    Ozsoydan, F.B., Baykasoglu, A.: A swarm intelligence-based algorithm for the set-union knapsack problem. Future Gen. Comput. Syst. 93, 560–569 (2019)CrossRefGoogle Scholar

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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.College of Mathematics and Data ScienceMinjiang UniversityFuzhouChina

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