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Title: | Detecting potential design weaknesses in shade through network feature analysis | ||||||||||
Author: | Viktorin, Adam; Pluháček, Michal; Šenkeřík, Roman; Kadavý, Tomáš | ||||||||||
Document type: | Conference paper (English) | ||||||||||
Source document: | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2017, vol. 10334 LNCS, p. 662-673 | ||||||||||
ISSN: | 0302-9743 (Sherpa/RoMEO, JCR) | ||||||||||
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ISBN: | 978-3-319-59650-1 | ||||||||||
DOI: | https://doi.org/10.1007/978-3-319-59650-1_56 | ||||||||||
Abstract: | This preliminary study presents a hybridization of two research fields – evolutionary algorithms and complex networks. A network is created by the dynamic of an evolutionary algorithm, namely Success-History based Adaptive Differential Evolution (SHADE). Network feature, node degree centrality, is used afterward to detect potential design weaknesses of SHADE algorithm. This approach is experimentally tested on the CEC2015 benchmark set of test functions and future directions in the research are proposed. © Springer International Publishing AG 2017. | ||||||||||
Full text: | https://link.springer.com/chapter/10.1007/978-3-319-59650-1_56 | ||||||||||
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