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A Survey of Group Intelligence Optimization Algorithms

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Cyber Security Intelligence and Analytics (CSIA 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 928))

Abstract

The group intelligent optimization algorithm provides some new ideas for solving many practical problems. These algorithms have stronger robustness and stronger search ability, and are easy to implement in parallel. It is easy to combine with other algorithms to improve the performance of the algorithm and solve complex practical problems. The effect of the experiment is more obvious. In this paper, the improvement and application of particle swarm optimization algorithm, fireworks algorithm and artificial bee colony algorithm in intelligent algorithm are reviewed, and the advantages and disadvantages are analyzed. The future development of intelligent algorithm is prospected.

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Acknowledgments

This research was supported by the National Natural Science Foundation of China (Project No. 51678375), Natural Science Foundation of Liaoning Province (Project No. 2015020603), and the basic scientific research project of Liaoning Higher Education (Project No. LJZ2017009).

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Authors and Affiliations

  1. School of Management, Shenyang Jianzhu University, Shenyang, 110168, China

    Chunguang Chang & Xi Wu

Authors
  1. Chunguang Chang
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  2. Xi Wu
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Corresponding author

Correspondence to Xi Wu .

Editor information

Editors and Affiliations

  1. Shanghai University, Shanghai, China

    Zheng Xu

  2. University of Texas at San Antonio, San Antonio, TX, USA

    Kim-Kwang Raymond Choo

  3. University of Guelph, Guelph, ON, Canada

    Ali Dehghantanha

  4. Kennesaw State University, Marietta, GA, USA

    Reza Parizi

  5. Manchester Metropolitan University, Stockport, UK

    Mohammad Hammoudeh

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Chang, C., Wu, X. (2020). A Survey of Group Intelligence Optimization Algorithms. In: Xu, Z., Choo, KK., Dehghantanha, A., Parizi, R., Hammoudeh, M. (eds) Cyber Security Intelligence and Analytics. CSIA 2019. Advances in Intelligent Systems and Computing, vol 928. Springer, Cham. https://doi.org/10.1007/978-3-030-15235-2_136

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