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Shade mutation strategy analysis via dynamic simulation in complex network

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dc.title Shade mutation strategy analysis via dynamic simulation in complex network en
dc.contributor.author Viktorin, Adam
dc.contributor.author Šenkeřík, Roman
dc.contributor.author Pluháček, Michal
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 299
dc.citation.epage 305
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 10.7148/2017-0299
dc.relation.uri http://www.scs-europe.net/dlib/2017/2017-0299.htm
dc.relation.uri http://www.scs-europe.net/dlib/2017/ecms2017acceptedpapers/0299-is_ECMS2017_0127.pdf
dc.subject Differential Evolution en
dc.subject SHADE en
dc.subject Complex Network en
dc.subject Mutation en
dc.description.abstract This paper presents a novel approach to visualizing Evolutionary Algorithm (EA) dynamic in complex network and analyses the greediness of "current-topbest/1" mutation strategy used in state-of-art Differential Evolution (DE) algorithm-Success-History based Adaptive DE (SHADE) on CEC2015 benchmark set of test functions. Provided analysis suggests that the greediness might not be the optimal approach for guiding the evolution. © 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/10563/1007244
utb.identifier.obdid 43877061
utb.identifier.scopus 2-s2.0-85021783214
utb.identifier.wok 000404420000045
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 Viktorin, Adam
utb.contributor.internalauthor Šenkeřík, Roman
utb.contributor.internalauthor Pluháček, Michal
utb.contributor.internalauthor Kadavý, Tomáš
utb.fulltext.affiliation Adam Viktorin Roman Senkerik Michal Pluhacek Tomas Kadavy Tomas Bata University in Zlin, Faculty of Applied Informatics Nam T.G. Masaryka 5555, 760 01 Zlin, Czech Republic {aviktorin, senkerik, pluhacek, kadavy}@fai.utb.cz
utb.fulltext.dates -
utb.fulltext.references Brest, J., Greiner, S., Boskovic, B., Mernik, M., & Zumer, V. (2006). Self-adapting control parameters in differential evolution: A comparative study on numerical benchmark prob-lems. IEEE transactions on evolutionary computation, 10(6), 646-657. Brest, J., Korošec, P., Šilc, J., Zamuda, A., Bošković, B., & Maučec, M. S. (2013). Differen-tial evolution and differential ant-stigmergy on dynamic optimisation problems. International Journal of Systems Science, 44(4), 663-679. Das, S., Abraham, A., Chakraborty, U. K., & Konar, A. (2009). Differential evolution using a neighborhoodbased mutation operator. IEEE Transactions on Evolutionary Computa-tion, 13(3), 526-553. Das, S., Mullick, S. S., & Suganthan, P. N. (2016). Recent advances in differential evolution–An updated survey. Swarm and Evolutionary Computation, 27, 1-30. Mallipeddi, R., Suganthan, P. N., Pan, Q. K., & Tasgetiren, M. F. (2011). Differential evolu-tion algorithm with ensemble of parameters and mutation strategies. Applied Soft Compu-ting, 11(2), 1679-1696. Mininno, E., Neri, F., Cupertino, F., & Naso, D. (2011). Compact differential evolution. IEEE Transactions on Evolutionary Computation, 15(1), 32-54. Neri, F., & Tirronen, V. (2010). Recent advances in differential evolution: a survey and exper-imental analysis. Artificial Intelligence Review, 33(1-2), 61-106. Pluhacek, M., Janostik, J., Senkerik, R., & Zelinka, I. (2016). 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. Qin, A. K., Huang, V. L., & Suganthan, P. N. (2009). Differential evolution algorithm with strategy adaptation for global numerical optimization. IEEE transactions on Evolutionary Computation, 13(2), 398-417. Storn, R., & Price, K. (1995). Differential evolution-a simple and efficient adaptive scheme for global optimization over continuous spaces (Vol. 3). Berkeley: ICSI. Tanabe, R., & Fukunaga, A. (2013). Success-history based parameter adaptation for differential evolution. In Evolutionary Computation (CEC), 2013 IEEE Congress on (pp. 71-78). IEEE. Tanabe, R., & Fukunaga, A. S. (2014). Improving the search performance of SHADE using linear population size reduction. In Evolutionary Computation (CEC), 2014 IEEE Con-gress on (pp. 1658-1665). IEEE. Viktorin, A., Pluhacek, M., & Senkerik, R. (2016). Network Based Linear Population Size Reduction in SHADE. In Intelligent Networking and Collaborative Systems (INCoS), 2016 International Conference on (pp. 86-93). IEEE. Zhang, J., & Sanderson, A. C. (2009). JADE: adaptive differential evolution with optional external archive. Evolutionary Computation, IEEE Transactions on, 13(5), 945-958.
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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