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Archive analysis in SHADE

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Title: Archive analysis in SHADE
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). 2017, vol. 10246 LNAI, p. 688-699
ISSN: 0302-9743 (Sherpa/RoMEO, JCR)
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ISBN: 978-3-319-59059-2
DOI: https://doi.org/10.1007/978-3-319-59060-8_62
Abstract: The aim of this research paper is to analyze the current optional archive in Success-History based Adaptive Differential Evolution (SHADE) which is used during mutation. The usefulness of the archive is analyzed on CEC 2015 benchmark set of test functions where the impact of successful archive use on final test function value is studied. This paper also proposes a new version of optional archive named Enhanced Archive (EA), which is also tested on CEC 2015 benchmark set and the results are compared with the canonical version. Two research questions are discussed: Whether SHADE with EA has better performance than canonical SHADE and whether it makes a better use of the archive. © Springer International Publishing AG 2017.
Full text: https://link.springer.com/chapter/10.1007/978-3-319-59060-8_62
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Citace článku v konferenčním sborníku:
VIKTORIN, Adam, Roman ŠENKEŘÍK, Michal PLUHÁČEK a Tomáš KADAVÝ. Archive analysis in SHADE. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) [online]. Zakopane: Springer Verlag, 2017, s. 688-699. [cit. 2024-11-22]. ISSN 0302-9743. Dostupné z: https://link.springer.com/chapter/10.1007/978-3-319-59060-8_62.

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