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How distance based parameter adaptation affects population diversity

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dc.title How distance based parameter adaptation affects population diversity en
dc.contributor.author Viktorin, Adam
dc.contributor.author Šenkeřík, Roman
dc.contributor.author Pluháček, Michal
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 978-3-319-91640-8
dc.date.issued 2018
utb.relation.volume 10835 LNCS
dc.citation.spage 307
dc.citation.epage 319
dc.event.title 8th International Conference on Bioinspired Optimization Methods and Their Applications, BIOMA 2018
dc.event.location Paris
utb.event.state-en France
utb.event.state-cs Francie
dc.event.sdate 2018-05-16
dc.event.edate 2018-05-18
dc.type conferenceObject
dc.language.iso en
dc.publisher Springer Verlag
dc.identifier.doi 10.1007/978-3-319-91641-5_26
dc.relation.uri https://link.springer.com/chapter/10.1007/978-3-319-91641-5_26
dc.subject Distance-based parameter adaptation en
dc.subject SHADE en
dc.subject Population diversity en
dc.description.abstract This paper discusses the effect of distance based parameter adaptation on the population diversity of the Success-History based Adaptive Differential Evolution (SHADE). The distance-based parameter adaptation was designed to promote exploration over exploitation and provide better search capabilities of the SHADE algorithm in higher dimensional objective spaces. The population diversity is recorded on the 15 test functions from the CEC 2015 benchmark set in two-dimensional settings, 10D and 30D, to provide the empiric evidence of a beneficial influence of the distance based parameter adaptation in comparison with the objective function value based approach. © 2018, Springer International Publishing AG, part of Springer Nature. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1007998
utb.identifier.obdid 43878843
utb.identifier.scopus 2-s2.0-85047494996
utb.identifier.wok 000554401600026
utb.source d-scopus
dc.date.accessioned 2018-07-27T08:47:38Z
dc.date.available 2018-07-27T08:47:38Z
dc.description.sponsorship Ministry of Education; CA15140, COST, European Cooperation in Science and Technology; IC406, COST, European Cooperation in Science and Technology; IGA/CebiaTech/2018/003; MSMT-7778/2014; LO1303; CZ.1.05/2.1.00/03.0089, FEDER, European Regional Development Fund; COST, European Cooperation in Science and Technology
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) [Action CA15140, Action IC406]
utb.ou CEBIA-Tech
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 ( ✉ ) http://orcid.org/0000-0003-0861-0340 , Roman Senkerik http://orcid.org/0000-0002-5839-4263 , Michal Pluhacek http://orcid.org/0000-0002-3692-2838 , 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 {aviktorin,senkerik,pluhacek,kadavy}@utb.cz
utb.fulltext.dates -
utb.fulltext.references 1. Price, K., Storn, R.: Differential evolution-a simple and efficient adaptive scheme for global optimization over continuous space. Technical report, International Computer Science Institute (1995) 2. Gämperle, R., Müller, S.D., Koumoutsakos, P.: A parameter study for differential evolution. Adv. Intell. Syst. Fuzzy Syst. Evol. Comput. 10(10), 293–298 (2002) 3. Liu, J.: On setting the control parameter of the differential evolution method. In: Proceedings of the 8th International Conference on Soft Computing (MENDEL 2002), pp. 11–18 (2002) 4. Wolpert, D.H., Macready, W.G.: No free lunch theorems for optimization. IEEE Trans. Evol. Comput. 1(1), 67–82 (1997) 5. Das, S., Mullick, S.S., Suganthan, P.N.: Recent advances in differential evolution-an updated survey. Swarm Evol. Comput. 27, 1–30 (2016) 6. Tanabe, R., Fukunaga, A.: Success-history based parameter adaptation for differential evolution. In: 2013 IEEE Congress on Evolutionary Computation (CEC), pp. 71–78. IEEE (2013) 7. 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) 8. Guo, S.M., Tsai, J.S.H., Yang, C.C., Hsu, P.H.: A self-optimization approach for l-shade incorporated with eigenvector-based crossover and successful-parent-selecting framework on CEC 2015 benchmark set. In: 2015 IEEE Congress on Evolutionary Computation (CEC), pp. 1003–1010. IEEE (2015) 9. Awad, N.H., Ali, M.Z., Suganthan, P.N., Reynolds, R.G.: An ensemble sinusoidal parameter adaptation incorporated with l-shade for solving CEC 2014 benchmark problems. In: 2016 IEEE Congress on Evolutionary Computation (CEC), pp. 2958–2965. IEEE (2016) 10. Brest, J., Maučec, M.S., Bošković, B.: Single objective real-parameter optimization: algorithm jSO. In: 2017 IEEE Congress on Evolutionary Computation (CEC), pp. 1311–1318. IEEE (2017) 11. Yang, M., Li, C., Cai, Z., Guan, J.: Differential evolution with auto-enhanced population diversity. IEEE Trans. Cybern. 45(2), 302–315 (2015) 12. Zhang, C., Zhao, Z., Yang, T., Fan, B.: Adaptive differential evolution with coordinated crossover and diversity-based population. In: 2016 12th IEEE International Conference on Control and Automation (ICCA), pp. 947–950. IEEE (2016) 13. Zhao, L., Sun, C., Huang, X., Zhou, B.: Differential evolution with strategy of improved population diversity. In: 2016 35th Chinese Control Conference (CCC), pp. 2784–2787. IEEE (2016) 14. Poláková, R., Tvrdík, J., Bujok, P.: Population-size adaptation through diversity-control mechanism for differential evolution. In: Proceedings of the 22nd International Conference on Soft Computing (MENDEL 2016), pp. 49–56 (2016) 15. Zhang, J., Sanderson, A.C.: JADE: adaptive differential evolution with optional external archive. IEEE Trans. Evol. Comput. 13(5), 945–958 (2009)
utb.fulltext.sponsorship This work was supported by the Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme Project no. LO1303 (MSMT-7778/2014), further 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/2018/003. This work is also based upon support by COST (European Cooperation in Science & Technology) under Action CA15140, Improving Applicability of Nature-Inspired Optimisation by Joining Theory and Practice (ImAppNIO), and Action IC406, High-Performance Modelling and Simulation for Big Data Applications (cHiPSet).
utb.wos.affiliation [Viktorin, Adam; Senkerik, Roman; Pluhacek, Michal; 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 LO1303 (MSMT-7778/2014)
utb.fulltext.projects CZ.1.05/2.1.00/03.0089
utb.fulltext.projects IGA/CebiaTech/2018/003
utb.fulltext.projects CA15140
utb.fulltext.projects ImAppNIO
utb.fulltext.projects cHiPSet
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