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Title: | New running technique for the bison algorithm | ||||||||||
Author: | Kazíková, Anežka; Pluháček, Michal; Viktorin, Adam; Šenkeřík, Roman | ||||||||||
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. 10841 LNAI, p. 417-426 | ||||||||||
ISSN: | 0302-9743 (Sherpa/RoMEO, JCR) | ||||||||||
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ISBN: | 978-3-319-91252-3 | ||||||||||
DOI: | https://doi.org/10.1007/978-3-319-91253-0_39 | ||||||||||
Abstract: | This paper examines the performance of the Bison Algorithm with a new running technique. The Bison Algorithm was inspired by the typical behavior of bison herds: the swarming movement of endangered bison as the exploitation factor and the running as the exploration phase of the optimization. While the original running procedure allowed the running groupto scatter throughout the search space, the new approach proposed in this paper preserves the initial formation of the running group throughout the optimization process. At the beginning of the paper, we introduce the Bison Algorithm and explain the new running technique procedure. Later the performance of the adjusted algorithm is tested and compared to the Particle Swarm Optimization and the Cuckoo Search algorithm on the IEEE CEC 2017 benchmark set, consisting of 30 functions. Finally, we evaluate the meaning of the experiment outcomes for future research. © Springer International Publishing AG, part of Springer Nature 2018. | ||||||||||
Full text: | https://link.springer.com/chapter/10.1007/978-3-319-91253-0_39 | ||||||||||
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