Abstract
This paper presents an initial proposal of methodology for converting the inner dynamics of PSO algorithm into complex network. The motivation is in the recent trend of adaptive 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 methodology described in this paper manages to put significant amount of information about the inner dynamics of PSO algorithm into a complex network.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Kennedy, J., Eberhart, R.: Particle swarm optimization. In: IEEE International Conference on Neural Networks, pp. 1942–1948 (1995)
Kennedy, J., Eberhart, R.C., Shi, Y.: Swarm Intelligence. Morgan Kaufmann Publishers (2001)
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)
Yuhui, S., Eberhart, R.: A modified particle swarm optimizer. In: IEEE World Congress on Computational Intelligence, 4–9 May 1998, pp. 69–73
Zelinka, I., Davendra, D., Enkek, R., Jaek, R.: Do evolutionary algorithm dynamics create complex network structures? Complex Syst. 2, 0891–2513, 20, 127–140
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)
Zelinka, I.: Investigation on relationship between complex network and evolutionary algorithms dynamics. AIP Conf. Proc. 1389(1), 1011–1014 (2011)
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, pp. 161–174. Springer, Berlin, Heidelberg (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 Dec 2014
Acknowledgments
This work was supported by Grant Agency of the Czech Republic - GACR P103/15/06700S, further by financial support of research project NPU I No. MSMT-7778/2014 by the Ministry of Education of the Czech Republic and also by the European Regional Development Fund under the Project CEBIA-Tech No. CZ.1.05/2.1.00/03.0089, partially supported by Grant of SGS No. SP2015/142 and SP2015/141 of VSB - Technical University of Ostrava, Czech Republic and by Internal Grant Agency of Tomas Bata University under the projects No. IGA/FAI/2015/057 and IGA/FAI/2015/061.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Pluhacek, M., Janostik, J., Senkerik, R., Zelinka, I., Davendra, D. (2016). PSO as Complex Network—Capturing the Inner Dynamics—Initial Study. In: Abraham, A., Wegrzyn-Wolska, K., Hassanien, A., Snasel, V., Alimi, A. (eds) Proceedings of the Second International Afro-European Conference for Industrial Advancement AECIA 2015. Advances in Intelligent Systems and Computing, vol 427. Springer, Cham. https://doi.org/10.1007/978-3-319-29504-6_51
Download citation
DOI: https://doi.org/10.1007/978-3-319-29504-6_51
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-29503-9
Online ISBN: 978-3-319-29504-6
eBook Packages: EngineeringEngineering (R0)