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dc.title | Particle swarm optimization with single particle repulsivity for multi-modal optimization | en |
dc.contributor.author | Pluháček, Michal | |
dc.contributor.author | Šenkeřík, Roman | |
dc.contributor.author | Viktorin, Adam | |
dc.contributor.author | Kadavý, Tomáš | |
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 Scopus Sources, Sherpa/RoMEO, JCR | |
dc.identifier.isbn | 978-3-319-91252-3 | |
dc.date.issued | 2018 | |
utb.relation.volume | 10841 LNAI | |
dc.citation.spage | 486 | |
dc.citation.epage | 494 | |
dc.event.title | 17th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2018 | |
dc.event.location | Zakopane | |
utb.event.state-en | Poland | |
utb.event.state-cs | Polsko | |
dc.event.sdate | 2018-06-03 | |
dc.event.edate | 2018-06-07 | |
dc.type | conferenceObject | |
dc.language.iso | en | |
dc.publisher | Springer Verlag | |
dc.identifier.doi | 10.1007/978-3-319-91253-0_45 | |
dc.relation.uri | https://link.springer.com/chapter/10.1007/978-3-319-91253-0_45 | |
dc.subject | Particle Swarm Optimization | en |
dc.subject | PSO | en |
dc.subject | Convergence | en |
dc.subject | Repulsivity | en |
dc.description.abstract | This work presents a simple but effective modification of the velocity updating formula in the Particle Swarm Optimization algorithm to improve the performance of the algorithm on multi-modal problems. The well-known issue of premature swarm convergence is addressed by a repulsive mechanism implemented on a single-particle level where each particle in the population is partially repulsed from a different particle. This mechanism manages to prolong the exploration phase and helps to avoid many local optima. The method is tested on well-known and typically used benchmark functions, and the results are further tested for statistical significance. © Springer International Publishing AG, part of Springer Nature 2018. | en |
utb.faculty | Faculty of Applied Informatics | |
dc.identifier.uri | http://hdl.handle.net/10563/1008000 | |
utb.identifier.obdid | 43878971 | |
utb.identifier.scopus | 2-s2.0-85048045984 | |
utb.identifier.wok | 000552718500045 | |
utb.source | d-scopus | |
dc.date.accessioned | 2018-07-27T08:47:39Z | |
dc.date.available | 2018-07-27T08:47:39Z | |
dc.description.sponsorship | IC1406, COST, European Cooperation in Science and Technology; CA15140, COST, European Cooperation in Science and Technology; IGA/CebiaTech/2018/003; MSMT-7778/2014, MŠMT, Ministerstvo Školství, Mládeže a Tělovýchovy; LO1303, MŠMT, Ministerstvo Školství, Mládeže a Tělovýchovy; COST, European Cooperation in Science and Technology; CZ.1.05/2.1.00/03.0089, FEDER, European Regional Development Fund | |
dc.description.sponsorship | 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/2018/003]; COST (European Cooperation in Science Technology) [CA15140, IC1406] | |
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 ( ✉ ) http://orcid.org/0000-0002-3692-2838 , Roman Senkerik http://orcid.org/0000-0002-5839-4263 , Adam Viktorin http://orcid.org/0000-0003-0861-0340 , and Tomas Kadavy http://orcid.org/0000-0002-3341-4336 Faculty of Applied Informatics, Tomas Bata University in Zlin, T. G. Masaryka 5555, 760 01 Zlin, Czech Republic {pluhacek,senkerik,aviktorin,kadavy}@utb.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. Eberhart, R.C., Shi, Y.: Comparing inertia weights and constriction factors in particle swarm optimization. In: Proceedings of the IEEE Congress on Evolutionary Computation, San Diego, USA, pp. 84–88 (2000) 6. Van Den Bergh, F., Engelbrecht, A.P.: A study of particle swarm optimization particle trajectories. Inf. Sci. 176(8), 937–971 (2006) 7. Riget, J., Vesterstrøm, J.S.: A diversity-guided particle swarm optimizer-the ARPSO. Technical Report, vol. 2, p. 2002. Department of Computer Science, University of Aarhus, Aarhus, Denmark (2002) 8. Han, F., Liu, Q.: An improved hybrid PSO based on ARPSO and the Quasi-Newton method. In: Tan, Y., Shi, Y., Buarque, F., Gelbukh, A., Das, S., Engelbrecht, A. (eds.) ICSI 2015. LNCS, vol. 9140, pp. 460–467. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-20466-6 48 9. Engelbrecht, A.P.: Particle swarm optimization: iteration strategies revisited. In: 2013 BRICS Congress on Computational Intelligence and 11th Brazilian Congress on Computational Intelligence, Ipojuca, pp. 119–123 (2013) | |
utb.fulltext.sponsorship | - | |
utb.wos.affiliation | [Pluhacek, Michal; Senkerik, Roman; Viktorin, Adam; Kadavy, Tomas] Tomas Bata Univ Zlin, Fac Appl Informat, TG Masaryka 5555, Zlin 76001, Czech Republic | |
utb.scopus.affiliation | Faculty of Applied Informatics, Tomas Bata University in Zlin, T. G. Masaryka 5555, Zlin, Czech Republic | |
utb.fulltext.projects | - |