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A lightweight SHADE-based algorithm for global optimization - liteSHADE

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dc.title A lightweight SHADE-based algorithm for global optimization - liteSHADE en
dc.contributor.author Viktorin, Adam
dc.contributor.author Šenkeřík, Roman
dc.contributor.author Pluháček, Michal
dc.contributor.author Kadavý, Tomáš
dc.contributor.author Jašek, Roman
dc.relation.ispartof Lecture Notes in Electrical Engineering
dc.identifier.issn 1876-1100 Scopus Sources, Sherpa/RoMEO, JCR
dc.identifier.isbn 9783030149062
dc.date.issued 2020
utb.relation.volume 554
dc.citation.spage 197
dc.citation.epage 206
dc.event.title 5th International Conference on Advanced Engineering Theory and Applications, AETA 2018
dc.event.location Ostrava
utb.event.state-en Czech Republic
utb.event.state-cs Česká republika
dc.event.sdate 2018-09-11
dc.event.edate 2018-09-13
dc.type conferenceObject
dc.language.iso en
dc.publisher Springer Verlag
dc.identifier.doi 10.1007/978-3-030-14907-9_20
dc.relation.uri https://link.springer.com/chapter/10.1007/978-3-030-14907-9_20
dc.subject Differential Evolution en
dc.subject liteSHADE en
dc.subject SHADE en
dc.subject Simplification en
dc.description.abstract In this paper, a novel lightweight version of the Successful-History based Adaptive Differential Evolution (SHADE) is presented as the first step towards a simple, user-friendly, metaheuristic algorithm for global optimization. This simplified algorithm is called liteSHADE and is compared to the original SHADE on the CEC2015 benchmark set in three dimensional settings – 10D, 30D and 50D. The results support the idea, that simplification may lead to a successful and understandable algorithm with competitive or even better performance. © Springer Nature Switzerland AG 2020. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1008756
utb.identifier.obdid 43881237
utb.identifier.scopus 2-s2.0-85066338041
utb.source d-scopus
dc.date.accessioned 2019-08-13T10:17:18Z
dc.date.available 2019-08-13T10:17:18Z
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.contributor.internalauthor Jašek, Roman
utb.fulltext.affiliation Adam Viktorin, Roman Senkerik, Michal Pluhacek, Tomas Kadavy, Roman Jasek Faculty of Applied Informatics, Tomas Bata University in Zlin, T. G. Masaryka 5555, 760 01 Zlin, Czech Republic {aviktorin,senkerik,pluhacek,kadavy,jasek}@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/2019/002. 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 Faculty of Applied Informatics, Tomas Bata University in Zlin, T. G. Masaryka 5555, Zlin, 760 01, Czech Republic
utb.fulltext.projects LO1303
utb.fulltext.projects CZ.1.05/2.1.00/03.0089
utb.fulltext.projects IGA/CebiaTech/2019/002
utb.fulltext.projects CA15140
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
utb.fulltext.faculty Faculty of Applied Informatics
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