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Title: | How distance based parameter adaptation affects population diversity | ||||||||||
Author: | Viktorin, Adam; Šenkeřík, Roman; Pluháček, Michal; 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). 2018, vol. 10835 LNCS, p. 307-319 | ||||||||||
ISSN: | 0302-9743 (Sherpa/RoMEO, JCR) | ||||||||||
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ISBN: | 978-3-319-91640-8 | ||||||||||
DOI: | https://doi.org/10.1007/978-3-319-91641-5_26 | ||||||||||
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. | ||||||||||
Full text: | https://link.springer.com/chapter/10.1007/978-3-319-91641-5_26 | ||||||||||
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