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PSO with partial population restart based on complex network analysis

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dc.title PSO with partial population restart based on complex network analysis en
dc.contributor.author Pluháček, Michal
dc.contributor.author Viktorin, Adam
dc.contributor.author Šenkeřík, Roman
dc.contributor.author Kadavý, Tomáš
dc.contributor.author Zelinka, Ivan
dc.relation.ispartof Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.identifier.issn 0302-9743 OCLC, Ulrich, Sherpa/RoMEO, JCR
dc.identifier.isbn 978-3-319-59650-1
dc.identifier.isbn 978-3-319-59649-5
dc.date.issued 2017
utb.relation.volume 10334 LNCS
dc.citation.spage 183
dc.citation.epage 192
dc.event.title 12th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2017
dc.event.location Logroño (La Rioja)
utb.event.state-en Spain
utb.event.state-cs Španělsko
dc.event.sdate 2017-06-21
dc.event.edate 2017-06-23
dc.type conferenceObject
dc.language.iso en
dc.publisher Springer Verlag
dc.identifier.doi 10.1007/978-3-319-59650-1_16
dc.relation.uri https://link.springer.com/chapter/10.1007%2F978-3-319-59650-1_16
dc.subject Complex Network en
dc.subject Hybrid method en
dc.subject Particle Swarm Optimization en
dc.subject Swarm intelligence en
dc.description.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. © Springer International Publishing AG 2017. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1007264
utb.identifier.obdid 43877144
utb.identifier.scopus 2-s2.0-85021761713
utb.identifier.wok 000432880600016
utb.source d-scopus
dc.date.accessioned 2017-09-03T21:40:07Z
dc.date.available 2017-09-03T21:40:07Z
dc.description.sponsorship P103/15/06700S, GACR;GAČR, Grantová Agentura České Republiky
dc.description.sponsorship Grant Agency of the Czech Republic [GACR P103/15/06700S]; Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme [LO1303, MSMT-7778/2014]; European Regional Development Fund under the Project CEBIA-Tech [CZ.1.05/2.1.00/03.0089]; Internal Grant Agency of Tomas Bata University [IGA/CebiaTech/2017/004]
utb.contributor.internalauthor Pluháček, Michal
utb.contributor.internalauthor Viktorin, Adam
utb.contributor.internalauthor Šenkeřík, Roman
utb.contributor.internalauthor Kadavý, Tomáš
utb.fulltext.affiliation Michal Pluhacek 1 ✉ , Adam Viktorin 1 , Roman Senkerik 1 , Tomas Kadavy 1 , and Ivan Zelinka 2 1 Faculty of Applied Informatics, Tomas Bata University in Zlin, Nam T.G. Masaryka 5555, 760 01 Zlin, Czech Republic {pluhacek,aviktorin,senkerik,kadavy}@fai.utb.cz 2 Faculty of Electrical Engineering and Computer Science, Technical University of Ostrava, 17. listopadu 15, 708 33 Ostrava-Poruba, Czech Republic ivan.zelinka@vsb.cz
utb.fulltext.dates -
utb.fulltext.references 1. Kennedy, J., Eberhart, R.: Particle swarm optimization. In: Proceedings of the IEEE International Conference on Neural Networks, pp. 1942–1948 (1995) 2. 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) 3. Kennedy, J.: The particle swarm: social adaptation of knowledge. In: Proceedings of the IEEE International Conference on Evolutionary Computation, pp. 303–308 (1997) 4. 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 5. 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 6. Zelinka, I.: Investigation on relationship between complex network and evolutionary algorithms dynamics. In: AIP Conference Proceedings, vol. 1389, no. 1, pp. 1011–1014 (2011) 7. 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) 8. 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) 9. 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) 10. Newman, M.E.J.: The mathematics of networks. New Palgrave Encycl. Econ. 2(2008), 1–12 (2008) 11. Digalakis, J.G., Margaritis, K.G.: On benchmarking functions for genetic algorithms. Int. J. Comput. Math. 77(4), 481–506 (2001) 12. Dieterich, J.M., Hartke, B.: Empirical review of standard benchmark functions using evolutionary global optimization. arXiv preprint arXiv:1207.4318 (2012)
utb.fulltext.sponsorship 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.
utb.scopus.affiliation Faculty of Applied Informatics, Tomas Bata University in Zlin, Nam T.G. Masaryka 5555, Zlin, Czech Republic; Faculty of Electrical Engineering and Computer Science, Technical University of Ostrava, 17. listopadu 15, Ostrava-Poruba, Czech Republic
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