Archive analysis in SHADE
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F17%3A63517054" target="_blank" >RIV/70883521:28140/17:63517054 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-3-319-59060-8_62" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-319-59060-8_62</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-59060-8_62" target="_blank" >10.1007/978-3-319-59060-8_62</a>
Alternative languages
Result language
angličtina
Original language name
Archive analysis in SHADE
Original language description
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.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISBN
978-3-319-59059-2
ISSN
0302-9743
e-ISSN
neuvedeno
Number of pages
12
Pages from-to
688-699
Publisher name
Springer-Verlag Berlin
Place of publication
Heidelberg
Event location
Zakopane
Event date
Jun 11, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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