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dc.title | Randomization of individuals selection in differential evolution | en |
dc.contributor.author | Šenkeřík, Roman | |
dc.contributor.author | Pluháček, Michal | |
dc.contributor.author | Viktorin, Adam | |
dc.contributor.author | Kadavý, Tomáš | |
dc.contributor.author | Komínková Oplatková, Zuzana | |
dc.relation.ispartof | Advances in Intelligent Systems and Computing | |
dc.identifier.issn | 2194-5357 Scopus Sources, Sherpa/RoMEO, JCR | |
dc.identifier.isbn | 978-3-319-97887-1 | |
dc.date.issued | 2019 | |
utb.relation.volume | 837 | |
dc.citation.spage | 180 | |
dc.citation.epage | 191 | |
dc.event.title | 23rd International Conference on Soft Computing, MENDEL 2017 | |
dc.event.location | Brno | |
utb.event.state-en | Czech Republic | |
utb.event.state-cs | Česká republika | |
dc.event.sdate | 2017-06-20 | |
dc.event.edate | 2017-06-22 | |
dc.type | conferenceObject | |
dc.language.iso | en | |
dc.publisher | Springer Verlag | |
dc.identifier.doi | 10.1007/978-3-319-97888-8_16 | |
dc.relation.uri | https://link.springer.com/chapter/10.1007/978-3-319-97888-8_16 | |
dc.subject | Burgers map | en |
dc.subject | complex dynamics | en |
dc.subject | deterministic chaos | en |
dc.subject | differential evolution | en |
dc.subject | Lozi map | en |
dc.subject | randomization | en |
dc.description.abstract | This research deals with the hybridization of two computational intelligence fields, which are the chaos theory and evolutionary algorithms. Experiments are focused on the extensive investigation on the different randomization schemes for selection of individuals in differential evolution algorithm (DE). This research is focused on the hypothesis whether the different distribution of different pseudo-random numbers or the similar distribution additionally enhanced with hidden complex chaotic dynamics providing the unique sequencing are more beneficial to the heuristic performance. This paper investigates the utilization of the two-dimensional discrete chaotic systems, which are Burgers and Lozi maps, as the chaotic pseudo-random number generators (CPRNGs) embedded into the DE. Through the utilization of either chaotic systems or equal identified pseudo-random number distribution, it is possible to entirely keep or remove the hidden complex chaotic dynamics from the generated pseudo random data series. This research utilizes set of 4 selected simple benchmark functions, and five different randomizations schemes; further results are compared against canonical DE. © Springer Nature Switzerland AG 2019. | en |
utb.faculty | Faculty of Applied Informatics | |
dc.identifier.uri | http://hdl.handle.net/10563/1008174 | |
utb.identifier.obdid | 43880090 | |
utb.identifier.scopus | 2-s2.0-85051756818 | |
utb.source | d-scopus | |
dc.date.accessioned | 2018-08-30T13:31:26Z | |
dc.date.available | 2018-08-30T13:31:26Z | |
utb.contributor.internalauthor | Šenkeřík, Roman | |
utb.contributor.internalauthor | Pluháček, Michal | |
utb.contributor.internalauthor | Viktorin, Adam | |
utb.contributor.internalauthor | Kadavý, Tomáš | |
utb.contributor.internalauthor | Komínková Oplatková, Zuzana | |
utb.fulltext.affiliation | Roman Senkerik (✉) , Michal Pluhacek, Adam Viktorin, Tomas Kadavy, and Zuzana Kominkova Oplatkova Faculty of Applied Informatics, Tomas Bata University in Zlin, Nam T.G. Masaryka 5555, 760 01 Zlin, Czech Republic {senkerik,pluhacek,aviktorin,kadavy,oplatkova}@fai.utb.cz | |
utb.fulltext.dates | - | |
utb.fulltext.references | 1. Price, K.V., Storn, R.M., Lampinen, J.A.: Differential Evolution: A Practical Approach to Global Optimization, ser. Natural Computing Series. Springer, Berlin (2005) 2. Neri, F., Tirronen, V.: Recent advances in differential evolution: a survey and experimental analysis. Artif. Intell. Rev. 33(1–2), 61–106 (2010) 3. Das, S., Suganthan, P.N.: Differential evolution: a survey of the state-of-the-art. IEEE Trans. Evol. Comput. 15(1), 4–31 (2011) 4. Das, S., Mullick, S.S., Suganthan, P.: Recent advances in differential evolution – an updated survey. Swarm Evol. Comput. 27, 1–30 (2016) 5. Brest, J., Greiner, S., Bošković, B., Mernik, M., Zumer, V.: Self-adapting control parameters in differential evolution: a comparative study on numerical benchmark problems. IEEE Trans. Evol. Comput. 10(6), 646–657 (2006) 6. Qin, A.K., Huang, V.L., Suganthan, P.N.: Differential evolution algorithm with strategy adaptation for global numerical optimization. IEEE Trans. Evol. Comput. 13(2), 398–417 (2009) 7. Zhang, J., Sanderson, A.C.: JADE: adaptive differential evolution with optional external archive. IEEE Trans. Evol. Comput. 13(5), 945–958 (2009) 8. Das, S., Abraham, A., Chakraborty, U., Konar, A.: Differential evolution using a neighborhood-based mutation operator. IEEE Trans. Evol. Comput. 13(3), 526–553 (2009) 9. Mininno, E., Neri, F., Cupertino, F., Naso, D.: Compact differential evolution. IEEE Trans. Evol. Comput. 15(1), 32–54 (2011) 10. Mallipeddi, R., Suganthan, P.N., Pan, Q.K., Tasgetiren, M.F.: Differential evolution algorithm with ensemble of parameters and mutation strategies. Appl. Soft Comput. 11(2), 1679–1696 (2011) 11. Brest, J., Korosec, P., Silc, J., Zamuda, A., Boskovic, B., Maucec, M.S.: Differential evolution and differential ant-stigmergy on dynamic optimisation problems. Int. J. Syst. Sci. 44(4), 663–679 (2013) 12. Tanabe, R., Fukunaga, A.S.: Improving the search performance of SHADE using linear population size reduction. In: 2014 IEEE Congress on Evolutionary Computation (CEC), pp. 1658–1665. IEEE (2014) 13. Weber, M., Neri, F., Tirronen, V.: A study on scale factor in distributed differential evolution. Inf. Sci. 181(12), 2488–2511 (2011) 14. Neri, F., Iacca, G., Mininno, E.: Disturbed exploitation compact differential evolution for limited memory optimization problems. Inf. Sci. 181(12), 2469–2487 (2011) 15. Iacca, G., Caraffini, F., Neri, F.: Compact differential evolution light: high performance despite limited memory requirement and modest computational overhead. J. Comput. Sci. Technol. 27(5), 1056–1076 (2012) 16. Zamuda, A., Brest, J.: Self-adaptive control parameters’ randomization frequency and propagations in differential evolution. Swarm Evol. Comput. 25, 72–99 (2015) 17. Caponetto, R., Fortuna, L., Fazzino, S., Xibilia, M.G.: Chaotic sequences to improve the performance of evolutionary algorithms. IEEE Trans. Evol. Comput. 7(3), 289–304 (2003) 18. dos Santos Coelho, L., Mariani, V.C.: A novel chaotic particle swarm optimization approach using Hénon map and implicit filtering local search for economic load dispatch. Chaos, Solitons Fractals 39(2), 510–518 (2009) 19. Pluhacek, M., Senkerik, R., Davendra, D., Kominkova Oplatkova, Z., Zelinka, I.: On the behavior and performance of chaos driven PSO algorithm with inertia weight. Comput. Math Appl. 66(2), 122–134 (2013) 20. Pluhacek, M., Senkerik, R., Davendra, D.: Chaos particle swarm optimization with Eensemble of chaotic systems. Swarm Evol. Comput. 25, 29–35 (2015) 21. Metlicka, M., Davendra, D.: Chaos driven discrete artificial bee algorithm for location and assignment optimisation problems. Swarm Evol. Comput. 25, 15–28 (2015) 22. dos Santos Coelho, L., Ayala, H.V.H., Mariani, V.C.: A self-adaptive chaotic differential evolution algorithm using gamma distribution for unconstrained global optimization. Appl. Math. Comput. 234, 452–459 (2014) 23. Senkerik, R., Pluhacek, M., Zelinka, I., Davendra, D., Janostik, J.: Preliminary study on the randomization and sequencing for the chaos embedded heuristic. In: Abraham, A., Wegrzyn-Wolska, K., Hassanien, E.A., Snasel, V., Alimi, M.A. (eds.) Proceedings of the Second International Afro-European Conference for Industrial Advancement AECIA 2015, pp. 591–601. Springer International Publishing, Cham (2016) 24. Zelinka, I.: A survey on evolutionary algorithms dynamics and its complexity – mutual relations, past, present and future. Swarm Evol. Comput. 25, 2–14 (2015) 25. Sprott, J.C.: Chaos and Time-Series Analysis. Oxford University Press, Oxford (2003) 26. Senkerik, R., Pluhacek, M., Kominkova Oplatkova, Z., Davendra, D.: On the parameter settings for the chaotic dynamics embedded differential evolution. In: 2015 IEEE Congress on Evolutionary Computation (CEC), 25–28 May 2015, pp. 1410–1417 (2015) | |
utb.fulltext.sponsorship | This work was supported by Grant Agency of the Czech Republic - GACR P103/15/06700S, further by the 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, and by Internal Grant Agency of Tomas Bata University under the projects No. IGA/CEBIA-Tech/2017/004. | |
utb.scopus.affiliation | Faculty of Applied Informatics, Tomas Bata University in Zlin, Nam T.G. Masaryka 5555, Zlin, Czech Republic | |
utb.fulltext.projects | GACR P103/15/06700S | |
utb.fulltext.projects | MSMT-7778/2014 | |
utb.fulltext.projects | CZ.1.05/2.1.00/03.0089 | |
utb.fulltext.projects | IGA/CEBIA-Tech/2017/004 |