Clustering analysis of the population in Db_SHADE algorithm

Viktorin, Adam; Šenkeřík, Roman; Pluháček, Michal; Kadavý, Tomáš

dc.title	Clustering analysis of the population in Db_SHADE algorithm	en
dc.contributor.author	Viktorin, Adam
dc.contributor.author	Šenkeřík, Roman
dc.contributor.author	Pluháček, Michal
dc.contributor.author	Kadavý, Tomáš
dc.relation.ispartof	Mendel
dc.identifier.issn	1803-3814 Scopus Sources, Sherpa/RoMEO, JCR
dc.date.issued	2018
utb.relation.volume	24
utb.relation.issue	1
dc.citation.spage	9
dc.citation.epage	16
dc.type	article
dc.language.iso	en
dc.publisher	Brno University of Technology
dc.identifier.doi	10.13164/mendel.2018.1.009
dc.relation.uri	https://mendel-journal.org/index.php/mendel/article/view/13
dc.subject	DBSCAN	en
dc.subject	differential evolution	en
dc.subject	distance based parameter adaptation	en
dc.subject	SHADE	en
dc.description.abstract	This paper provides an analysis of the population clustering in a novel Success-History based Adaptive Differential Evolution algorithm with Distance based adaptation (Db_SHADE) in order to analyze the exploration and exploitation abilities of the algorithm. The comparison with the original SHADE algorithm is performed on the CEC2015 benchmark set in two dimensional settings (10D and 30D). The clustering analysis helps to answer the question about prolonged exploration phase of the Db_SHADE algorithm. Possible future research directions are drawn in the discussion and conclusion. © 2018, Brno University of Technology. All rights reserved.	en
utb.faculty	Faculty of Applied Informatics
dc.identifier.uri	http://hdl.handle.net/10563/1009089
utb.identifier.obdid	43881154
utb.identifier.scopus	2-s2.0-85072046299
utb.source	j-scopus
dc.date.accessioned	2019-09-19T07:56:15Z
dc.date.available	2019-09-19T07:56:15Z
dc.rights	Attribution-NonCommercial-ShareAlike 4.0 International
dc.rights.uri	https://creativecommons.org/licenses/by-nc-sa/4.0/
dc.rights.access	openAccess
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, Roman Senkerik, Michal Pluhacek, Tomas Kadavy Tomas Bata University in Zlin Faculty of Applied Informatics T. G. Masaryka 5555, 760 01 Zlin Czech Republic {aviktorin, senkerik, pluhacek, kadavy}@utb.cz
utb.fulltext.dates	-
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 IC1406, High-Performance Modelling and Simulation for Big Data Applications (cHiPSet). The work was further supported by resources of A.I.Lab at the Faculty of Applied Informatics, Tomas Bata University in Zlin (ailab.fai.utb.cz).
utb.scopus.affiliation	Tomas Bata University in Zlin, Faculty of Applied Informatics, T. G. Masaryka 5555, Zlin, 760 01, Czech Republic
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/2018/003
utb.fulltext.projects	CA15140
utb.fulltext.projects	IC1406
utb.fulltext.faculty	Faculty of Applied Informatics
utb.fulltext.faculty	Faculty of Applied Informatics
utb.fulltext.faculty	Faculty of Applied Informatics
utb.fulltext.faculty	Faculty of Applied Informatics