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Partial population restart of firefly algorithm using complex network analysis

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dc.title Partial population restart of firefly algorithm using complex network analysis en
dc.contributor.author Kadavý, Tomáš
dc.contributor.author Pluháček, Michal
dc.contributor.author Viktorin, Adam
dc.contributor.author Šenkeřík, Roman
dc.relation.ispartof 2017 IEEE Symposium Series on Computational Intelligence (SSCI)
dc.identifier.isbn 978-1-5386-2725-9
dc.date.issued 2017
utb.relation.volume 2018-January
dc.citation.spage 1
dc.citation.epage 7
dc.event.title IEEE Symposium Series on Computational Intelligence (IEEE SSCI)
dc.event.location Honolulu
utb.event.state-en Hawaii
utb.event.state-cs Havaj
dc.event.sdate 2017-11-27
dc.event.edate 2017-12-01
dc.type conferenceObject
dc.language.iso en
dc.publisher IEEE
dc.identifier.doi 10.1109/SSCI.2017.8285418
dc.relation.uri https://ieeexplore.ieee.org/abstract/document/8285418/
dc.subject Firefly Algorithm en
dc.subject FA en
dc.subject Complex Network en
dc.subject Population restart en
dc.description.abstract In this paper, we are presenting a method for controlling population diversity of popular metaheuristic algorithm, which is the Firefly Algorithm (FA). Presented method is using the advantages of complex networks and their several characteristics, that can be helpful for the detailed analysis of metaheuristic algorithm inner dynamic. However, this application can be quite tricky, since there are too many possibilities, as to how to use the advantages of complex networks analysis approach. Through this work, we are trying to present a simple workflow for building and analysis of network and the most suitable choices in each step to achieve better results of FA, especially, when focusing on population diversity. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1007911
utb.identifier.rivid RIV/70883521:28140/17:63517191!RIV18-GA0-28140___
utb.identifier.obdid 43877181
utb.identifier.scopus 2-s2.0-85046155457
utb.identifier.wok 000428251402080
utb.source d-wok
dc.date.accessioned 2018-05-18T15:12:07Z
dc.date.available 2018-05-18T15:12:07Z
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 [L01303 (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 Kadavý, Tomáš
utb.contributor.internalauthor Pluháček, Michal
utb.contributor.internalauthor Viktorin, Adam
utb.contributor.internalauthor Šenkeřík, Roman
utb.fulltext.affiliation Tomas Kadavy, Michal Pluhacek, Adam Viktorin, Roman Senkerik Faculty of Applied Informatics Tomas Bata University in Zlin T.G. Masaryka 5555, 760 01 Zlin, Czech Republic {kadavy,pluhacek,aviktorin,senkerik}@fai.utb.cz
utb.fulltext.dates -
utb.fulltext.references [1] X. S. Yang, Nature-Inspired Metaheuristic Algorithms, Luniver Press, UK, (2008). [2] X. S. Yang, Firefly algorithms for multimodal optimization, Proc. 5th Symposium on Stochastic Algorithms, Foundations and Applications, Lecture Notes in Computer Science, 5792: 169-178 (2009). [3] J. Kennedy and R. Eberhart, “Particle swarm optimization,” in Proceedings of the IEEE International Conference on Neural Networks, 1995, pp. 1942–1948. [4] J. Kennedy, “The particle swarm: social adaptation of knowledge,” in Proceedings of the IEEE International Conference on Evolutionary Computation, 1997, pp. 303–308. [5] J. Riget, J. Vesterstrom. A diversity-guided particle swarm optimizer-the ARPSO. Dept. Comput. Sci., Univ. of Aarhus, Aarhus, Denmark, Tech. Rep, 2002, 2: 2002. [6] Mandelbrot, Benoit B. (1982). The Fractal Geometry of Nature (Updated and augm. ed.). New York: W. H. Freeman. ISBN 0-7167-1186-9. [7] Xin-She Yang, Firefly Algorithm, Levy Flights and Global Optimization in Research and Development in Intelligent Systems XXVI, 2010, pp. 209-218. [8] Barrat, A., Barthelemy M., Vespignani A. Dynamical processes on complex networks. New York: Cambridge University Press, 2008. ISBN 9780521879507. [9] Otte, Evelien; Rousseau, Ronald (2002). "Social network analysis: a powerful strategy, also for the information sciences". Journal of Information Science. 28 (6): 441–453 [10] Kudělka, M., Zehnalová, Š., Horák, Z., Krömer, P., & Snášel, V. (2015). Local dependency in networks. International Journal of Applied Mathematics and Computer Science, 25(2), 281-293. [11] Pluhacek, M., Janostik, J., Senkerik, R., & Zelinka, I. (2016a). Converting PSO dynamics into complex network-Initial study. In T. Simos, & C. Tsitouras (Eds.), AIP Conference Proceedings (Vol. 1738, No. 1, p. 120021). AIP Publishing. [12] Pluhacek, M., Senkerik, R., Janostik, J., Viktorin, A., & Zelinka, I. (2016b). Study on swarm dynamics converted into complex network. In Proceedings-30th European Conference on Modelling and Simulation, ECMS 2016. European Council for Modelling and Simulation (ECMS). [13] Senkerik, R., Viktorin, A., Pluhacek, M., Janostik, J., & Davendra, D. (2016a). On the Influence of Different Randomization and Complex Network Analysis for Differential Evolution. In 2016 IEEE Congress on Evolutionary Computation (CEC) (pp. 3346-3353). IEEE. [14] Senkerik, R., Viktorin, A., Pluhacek, M., Janostik, J., & Oplatkova, Z. K. (2016b). Study on the Time Development of Complex Network for Metaheuristic. In Artificial Intelligence Perspectives in Intelligent Systems (pp. 525-533). Springer International Publishing. [15] M. Pluhacek, A. Viktorin, R. Senkerik, T. Kadavy, I. Zelinka. PSO with Partial Population Restart Based on Complex Network Analysis. In International Conference on Hybrid Artificial Intelligence Systems, 2017, pp. 183-192. [16] Janostik J., M. Pluhacek, R. Senkerik, I. Zelinka and F. Spacek. Capturing inner dynamics of firefly algorithm in complex network—initial study. In: Proceedings of the Second International Afro-European Conference for Industrial Advancement (AECIA 2015). Villejuif: Springer Verlag, 2016, s. 571-577. ISSN 2194-5357. [17] Newman, M.E.J.: The mathematics of networks. New Palgrave Encycl. Econ. 2(2008), 1–12.
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.wos.affiliation [Kadavy, Tomas; Pluhacek, Michal; Viktorin, Adam; Senkerik, Roman] Tomas Bata Univ Zlin, Fac Appl Informat, TG Masaryka 5555, Zlin 76001, Czech Republic
utb.fulltext.projects P103/15/06700S
utb.fulltext.projects LO1303 (MSMT-7778/2014)
utb.fulltext.projects CZ.1.05/2.1.00/03.0089
utb.fulltext.projects IGA/CebiaTech/2017/004
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