Abstract
This study presents a hybridization of Particle Swarm Optimization with a complex network creation and analysis. A partial population is performed in certain moments of the run of the algorithm based on the information obtained from a complex network structure that represents the communication in the population. We present initial results alongside statistical evaluation and discuss future possibilities of this approach.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Kennedy, J., Eberhart, R.: Particle swarm optimization. In: Proceedings of the IEEE International Conference on Neural Networks, pp. 1942–1948 (1995)
Shi, Y., Eberhart, R.: A modified particle swarm optimizer. In: Proceedings of the IEEE International Conference on Evolutionary Computation (IEEE World Congress on Computational Intelligence), pp. 69–73 (1998)
Kennedy, J.: The particle swarm: social adaptation of knowledge. In: Proceedings of the IEEE International Conference on Evolutionary Computation, pp. 303–308 (1997)
Nickabadi, A., Ebadzadeh, M.M., Safabakhsh, R.: A novel particle swarm optimization algorithm with adaptive inertia weight. Appl. Soft Comput. 11(4), 3658–3670 (2011). ISSN:1568-4946
Zelinka, I., Davendra, D., Enkek, R., Jaek, R.: Do evolutionary algorithm dynamics create complex network structures? Complex Syst. 20(2), 127–140 (2011). ISSN:0891–2513
Zelinka, I.: Investigation on relationship between complex network and evolutionary algorithms dynamics. In: AIP Conference Proceedings, vol. 1389, no. 1, pp. 1011–1014 (2011)
Zelinka, I., Davendra, D.D., Chadli, M., Senkerik, R., Dao, T.T., Skanderova, L.: Evolutionary dynamics as the structure of complex networks. In: Zelinka, I., Snasel, V., Abraham, A. (eds.) Handbook of Optimization. ISRL, vol. 38, pp. 215–243. Springer, Heidelberg (2013)
Davendra, D., Zelinka, I., Senkerik, R., Pluhacek, M.: Complex network analysis of discrete self-organising migrating algorithm. In: Zelinka, I., Suganthan, P., Chen, G., Snasel, V., Abraham, A., Rossler, O. (eds.) Nostradamus 2014: Prediction, Modeling and Analysis of Complex Systems. Advances in Intelligent Systems and Computing, vol. 289, pp. 161–174. Heidelberg, Springer (2014)
Davendra, D., Zelinka, I., Metlicka, M., Senkerik, R., Pluhacek, M.: Complex network analysis of differential evolution algorithm applied to flowshop with no-wait problem. In: 2014 IEEE Symposium on Differential Evolution (SDE), pp. 1–8, 9–12 December (2014)
Newman, M.E.J.: The mathematics of networks. New Palgrave Encycl. Econ. 2(2008), 1–12 (2008)
Digalakis, J.G., Margaritis, K.G.: On benchmarking functions for genetic algorithms. Int. J. Comput. Math. 77(4), 481–506 (2001)
Dieterich, J.M., Hartke, B.: Empirical review of standard benchmark functions using evolutionary global optimization. arXiv preprint arXiv:1207.4318 (2012)
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 Projects no. IGA/CebiaTech/2017/004.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Pluhacek, M., Viktorin, A., Senkerik, R., Kadavy, T., Zelinka, I. (2017). PSO with Partial Population Restart Based on Complex Network Analysis. In: MartÃnez de Pisón, F., Urraca, R., Quintián, H., Corchado, E. (eds) Hybrid Artificial Intelligent Systems. HAIS 2017. Lecture Notes in Computer Science(), vol 10334. Springer, Cham. https://doi.org/10.1007/978-3-319-59650-1_16
Download citation
DOI: https://doi.org/10.1007/978-3-319-59650-1_16
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-59649-5
Online ISBN: 978-3-319-59650-1
eBook Packages: Computer ScienceComputer Science (R0)