Harris Hawks Optimisation: Using of an Archive
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17310%2F21%3AA2202A0W" target="_blank" >RIV/61988987:17310/21:A2202A0W - isvavai.cz</a>
Result on the web
<a href="https://www.scopus.com/record/display.uri?eid=2-s2.0-85117512842&origin=resultslist&sort=plf-f&featureToggles=FEATURE_NEW_DOC_DETAILS_EXPORT:1" target="_blank" >https://www.scopus.com/record/display.uri?eid=2-s2.0-85117512842&origin=resultslist&sort=plf-f&featureToggles=FEATURE_NEW_DOC_DETAILS_EXPORT:1</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-87986-0_37" target="_blank" >10.1007/978-3-030-87986-0_37</a>
Alternative languages
Result language
angličtina
Original language name
Harris Hawks Optimisation: Using of an Archive
Original language description
This paper proposes an enhanced variant of the novel and popular Harris Hawks Optimisation (HHO) method. The original HHO algorithm was studied in many research projects, and a lot of hybrid (cooperative) variants of HHO was proposed. In this research study, an advanced HHO algorithm with an archive of the old solutions is proposed (HHOA). The proposed method is experimentally compared with the original HHO algorithm on a set of 22 real-world problems (CEC 2011). The results illustrate the superiority of HHOA because it outperforms HHO significantly in 20 out of 22 problems, and it is never significantly worse. Four well-known nature-based algorithms were employed to compare the efficiency of the proposed algorithm. HHOA achieves the best results in overall statistical comparison. A more detailed comparison shows that HHOA achieves the best results in half real-world problems, and it is never the worst-performing method. A newly employed archive of old solutions significantly increases the performance of the original HHO algorithm.
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
10102 - Applied mathematics
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2021
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 Artificial Intelligence 12854
ISBN
978-303087985-3
ISSN
0302-9743
e-ISSN
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Number of pages
9
Pages from-to
415-423
Publisher name
Springer
Place of publication
Cham, Switzerland
Event location
Zakopane, Polsko
Event date
Jun 20, 2021
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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