Abstract
This chapter presents an proposal of methodology for converting the inner dynamics of PSO algorithm into complex network. The motivation is in the recent trend of adaptive and learning methods for improving the performance of evolutionary computational techniques. It seems very likely that the complex network and its statistical characteristics can be used within those adaptive approaches. The network analysis also provides usefull insight into the inner dynamic of PSO. The methodology described in this chapter uses the communication in the swarm for construction of the network.
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Acknowledgements
This work was supported by Grant Agency of the Czech Republic GACR P103/15/06700S, further by the Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme Project no. LO1303 (MSMT-7778/2014. Also by the European Regional Development Fund under the Project CEBIA-Tech no. CZ.1.05/2.1.00/03.0089 and by Internal Grant Agency of Tomas Bata University under the Project no. IGA/CebiaTech/2016/007.
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Pluhacek, M., Šenkeřík, R., Viktorin, A., Kadavy, T. (2018). Complex Networks in Particle Swarm. In: Zelinka, I., Chen, G. (eds) Evolutionary Algorithms, Swarm Dynamics and Complex Networks. Emergence, Complexity and Computation, vol 26. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-55663-4_7
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DOI: https://doi.org/10.1007/978-3-662-55663-4_7
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