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dc.title | Distance based parameter adaptation for Success-History based Differential Evolution | en |
dc.contributor.author | Viktorin, Adam | |
dc.contributor.author | Šenkeřík, Roman | |
dc.contributor.author | Pluháček, Michal | |
dc.contributor.author | Kadavý, Tomáš | |
dc.contributor.author | Zamuda, Aleš | |
dc.relation.ispartof | Swarm and Evolutionary Computation | |
dc.identifier.issn | 2210-6502 Scopus Sources, Sherpa/RoMEO, JCR | |
dc.date.issued | 2019 | |
utb.relation.volume | 50 | |
dc.type | article | |
dc.language.iso | en | |
dc.publisher | Elsevier B.V. | |
dc.identifier.doi | 10.1016/j.swevo.2018.10.013 | |
dc.relation.uri | https://www.sciencedirect.com/science/article/pii/S2210650218303043 | |
dc.subject | differential evolution | en |
dc.subject | distance based | en |
dc.subject | parameter adaptation | en |
dc.subject | success-history | en |
dc.subject | scaling factor | en |
dc.subject | crossover rate | en |
dc.description.abstract | This paper proposes a simple, yet effective, modification to scaling factor and crossover rate adaptation in Success-History based Adaptive Differential Evolution (SHADE), which can be used as a framework to all SHADE-based algorithms. The performance impact of the proposed method is shown on the real-parameter single objective optimization (CEC2015 and CEC2017) benchmark sets in 10, 30, 50, and 100 dimensions for all SHADE, L-SHADE (SHADE with linear decrease of population size), and jSO algorithms. The proposed distance based parameter adaptation is designed to address the premature convergence of SHADE–based algorithms in higher dimensional search spaces to maintain a longer exploration phase. This design effectiveness is supported by presenting a population clustering analysis, along with a population diversity measure. Also, the new distance based algorithm versions (Db_SHADE, DbL_SHADE, and DISH) have obtained significantly better optimization results than their canonical counterparts (SHADE, L_SHADE, and jSO) in 30, 50, and 100 dimensional functions. © 2018 Elsevier B.V. | en |
utb.faculty | Faculty of Applied Informatics | |
dc.identifier.uri | http://hdl.handle.net/10563/1009431 | |
utb.identifier.obdid | 43880003 | |
utb.identifier.scopus | 2-s2.0-85057032118 | |
utb.identifier.wok | 000497252300020 | |
utb.source | j-scopus | |
dc.date.accessioned | 2019-11-20T10:30:42Z | |
dc.date.available | 2019-11-20T10:30:42Z | |
dc.description.sponsorship | Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme [101303 (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]; Slovenian Research AgencySlovenian Research Agency - Slovenia [P2-0041]; COST (European Cooperation in Science & Technology), Improving Applicability of NatureInspired Optimization by Joining Theory and Practice (ImAppNIO) [CA15140]; COST (European Cooperation in Science & Technology), High-Performance Modelling and Simulation for Big Data Applications (cHiPSet) [IC1406] | |
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 a, Roman Senkerik a,c, Michal Pluhacek a, Tomas Kadavy a, Ales Zamuda b* a Faculty of Applied Informatics, Tomas Bata University in Zlin, T. G. Masaryka 5555, 760 01 Zlin, Czech Republic b Faculty of Electrical Engineering and Computer Science, University of Maribor, Koroška Cesta 46, 2000 Maribor, Slovenia c Modeling Evolutionary Algorithms Simulation and Artificial Intelligence, Faculty of Electrical & Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City, Viet Nam ∗ Corresponding author. E-mail addresses: [email protected] (A. Viktorin), [email protected], [email protected] (R. Senkerik), [email protected] (M. Pluhacek), [email protected] (T. Kadavy), [email protected] (A. Zamuda). URL: https://ailab.fai.utb.cz (A. Viktorin). | |
utb.fulltext.dates | Received 13 April 2018 Received in revised form 26 October 2018 Accepted 29 October 2018 Available online 12 November 2018 | |
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 ), supported by the European Regional Development Fund under the Project CEBIA-Tech no. CZ.1.05/2.1.00/03.0089 , and supported by the Internal Grant Agency of Tomas Bata University under the Project No. IGA/CebiaTech/2018/003 . This work was also funded in part by the Slovenian Research Agency , Project No.: P2-0041 . This work is also based upon support by COST (European Cooperation in Science & Technology) under Action CA15140 , Improving Applicability of Nature-Inspired Optimization by Joining Theory and Practice (ImAppNIO), and Action IC1406 , High-Performance Modelling and Simulation for Big Data Applications (cHiPSet), and further supported by resources of the A.I.Lab at the Faculty of Applied Informatics, Tomas Bata University in Zlin (ailab.fai.utb.cz). | |
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; [Zamuda, Ales] Univ Maribor, Fac Elect Engn & Comp Sci, Koroska Cesta 46, Maribor 2000, Slovenia; [Senkerik, Roman] Ton Duc Thang Univ, Fac Elect & Elect Engn, Modeling Evolutionary Algorithms Simulat & Artifi, Ho Chi Minh City, Vietnam | |
utb.scopus.affiliation | Faculty of Applied Informatics, Tomas Bata University in Zlin, T. G. Masaryka 5555, Zlin, 760 01, Czech Republic; Faculty of Electrical Engineering and Computer Science, University of Maribor, Koroška Cesta 46, Maribor, 2000, Slovenia; Modeling Evolutionary Algorithms Simulation and Artificial Intelligence, Faculty of Electrical & Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City, Viet Nam | |
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 | P2-0041 | |
utb.fulltext.projects | CA15140 | |
utb.fulltext.projects | ImAppNIO | |
utb.fulltext.projects | IC1406 | |
utb.fulltext.projects | cHiPSet | |
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 |