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Uncovering communication density in PSO using complex network

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dc.title Uncovering communication density in PSO using complex network en
dc.contributor.author Pluháček, Michal
dc.contributor.author Šenkeřík, Roman
dc.contributor.author Viktorin, Adam
dc.contributor.author Kadavý, Tomáš
dc.relation.ispartof Proceedings - 31st European Conference on Modelling and Simulation, ECMS 2017
dc.identifier.isbn 9780993244049
dc.date.issued 2017
dc.citation.spage 306
dc.citation.epage 312
dc.event.title 31st European Conference on Modelling and Simulation, ECMS 2017
dc.event.location Budapest
utb.event.state-en Hungary
utb.event.state-cs Maďarsko
dc.event.sdate 2017-05-23
dc.event.edate 2017-05-26
dc.type conferenceObject
dc.language.iso en
dc.publisher European Council for Modelling and Simulation
dc.identifier.doi 10.7148/2017-0306
dc.relation.uri http://www.scs-europe.net/dlib/2017/2017-0306.htm
dc.relation.uri http://www.scs-europe.net/dlib/2017/ecms2017acceptedpapers/0306-is_ECMS2017_0128.pdf
dc.subject Swarm Intelligence en
dc.subject Particle Swarm Optimization en
dc.subject Complex Network en
dc.subject Swarm communication en
dc.description.abstract In this study, we investigate the communication in particle swarm optimization (PSO) by the means of network visualization. We measure the communication density of PSO optimizing four different benchmark functions. It is presented that the communication density varies over different fitness landscapes and in different phases of the optimizing process. We analyze the results in terms of use for future research. © ECMS Zita Zoltay Paprika, Péter Horák, Kata Váradi,Péter Tamás Zwierczyk, Ágnes Vidovics-Dancs, János Péter Rádics (Editors). en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1007245
utb.identifier.obdid 43877143
utb.identifier.scopus 2-s2.0-85021802660
utb.identifier.wok 000404420000046
utb.source d-scopus
dc.date.accessioned 2017-09-03T21:40:05Z
dc.date.available 2017-09-03T21:40:05Z
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 Šenkeřík, Roman
utb.contributor.internalauthor Viktorin, Adam
utb.contributor.internalauthor Kadavý, Tomáš
utb.fulltext.affiliation Michal Pluhacek, Roman Senkerik, Adam Viktorin and Tomas Kadavy Tomas Bata University in Zlin , Faculty of Applied Informatics Nam T.G. Masaryka 5555, 760 01 Zlin, Czech Republic {pluhacek, senkerik, aviktorin, kadavy}@fai.utb.cz
utb.fulltext.dates -
utb.fulltext.references Davendra, D., Zelinka, I, Metlicka, M., Senkerik, R., Pluhacek, M., "Complex network analysis of differential evolution algorithm applied to flowshop with no-wait problem," Differential Evolution (SDE), 2014 IEEE Symposium on , pp.1,8, 9-12 Dec. 2014 Davendra, D., Zelinka, I., Senkerik, R. and Pluhacek, M. Complex Network Analysis of Discrete Self-organising Migrating Algorithm, in: Zelinka, I. and Suganthan, P. and Chen, G. and Snasel, V. and Abraham, A. and Rossler, O. (Eds.) Nostradamus 2014: Prediction, Modeling and Analysis of Complex Systems, Advances in Intelligent Systems and Com-puting, Springer Berlin Heidelberg, pp. 161–174 (2014). Kennedy J. and Eberhart R., “Particle swarm optimization,” in Proceedings of the IEEE International Conference on Neural Networks, 1995, pp. 1942–1948. Kennedy J., “The particle swarm: social adaptation of knowledge,” in Proceedings of the IEEE International Conference on Evolutionary Computation, 1997, pp. 303–308.¨ Nickabadi A., Ebadzadeh M. M., Safabakhsh R., A novel particle swarm optimization algorithm with adaptive inertia weight, Applied Soft Computing, Volume 11, Issue 4, June 2011, Pages 3658-3670, ISSN 1568-4946 Senkerik, R., Viktorin, A., Pluhacek, M., Janostik, J. Oplatkova, Z. K. (2016). Study on the time development of complex network for metaheuristic. In Artificial Intelligence Perspectives in Intelligent Systems (pp. 525-533). Springer International Publishing. Shi Y. and Eberhart R., “A modified particle swarm optimizer,” in Proceedings of the IEEE International Conference on Evolutionary Computation (IEEE World Congress on Computational Intelligence), 1998, pp. 69–73.I. S. Volná, E. and Kotyrba, M. Unconventional heuristics for vehicle routing problems. Journal of Numerical Analysis, Industrial and Applied Mathematics. 2016, vol. 9-10, pp. 57-67. ISSN 1790-8140. Zelinka, I. Investigation on relationship between complex network and evolutionary algo-rithms dynamics, AIP Conference Proceedings 1389 (1) 1011–1014 2011a. Zelinka, I., Davendra, D., Enkek, R., Jaek, R.: Do Evolutionary Algorithm Dynamics Create Complex Network Structures? Complex Systems 2, 0891–2513, 20, 127–140, 2011b 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)
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 Tomas Bata University in Zlin, Faculty of Applied Informatics, Nam T.G. Masaryka 5555, Zlin, Czech Republic
utb.fulltext.projects GACR P103/15/06700S
utb.fulltext.projects LO1303
utb.fulltext.projects 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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