Slime mould algorithm: An experimental study of nature-inspired optimiser

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17310%2F22%3AA2302GVC" target="_blank" >RIV/61988987:17310/22:A2302GVC - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-3-031-21094-5_15" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-031-21094-5_15</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-21094-5_15" target="_blank" >10.1007/978-3-031-21094-5_15</a>

Result language
angličtina
Original language name
Slime mould algorithm: An experimental study of nature-inspired optimiser
Original language description
In this paper, the performance of the slime mould algorithms (SMA) is studied. The original SMA algorithm is enhanced by several mechanisms to achieve better results in various problems. The Eigen transformation, linear reduction of population size, and perturbation of the solution are proposed and combined together with various settings of control parameters. All 16 newly proposed variants of SMA are compared with the original SMA and 16 various nature-inspired methods. All the algorithms are applied to 22 real-world problems called CEC 2011. Achieved results illustrate the good performance of the newly proposed SMA variants, especially compared with the original SMA algorithm.
Czech name
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Czech description
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Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Bioinspired Optimization Methods and Their Applications
ISBN
978-3-031-21093-8
ISSN
—
e-ISSN
—
Number of pages
15
Pages from-to
1-15
Publisher name
Springer International Publishing AG, part of Springer Nature
Place of publication
Maribor, Slovenia
Event location
Maribor, Slovenia
Event date
Nov 17, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000771503500001

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