Towards the self-adaptation of the bat algorithm
Iztok Fister Jr.1; Simon Fong2; Janez Brest1; Iztok Fister1
Conference NameIASTED International Conference Artificial Intelligence and Applications (AIA 2014)
Source PublicationProceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2014
Conference DateFebruary 17 - 19, 2014
Conference PlaceInnsbruck, Austria

Bat algorithm is one of the younger members of swarm intelligence algorithms that was introduced by Yang in 2010. So far, several variants based on this algorithm have been proposed for coping with the continuous and discrete problems. This paper introduces a novel self-adaptive bat algorithm (SABA) that borrows the self-adapting mechanism from self-adapted differential evolution known under the name jDE. This algorithm was tested on ten benchmark functions taken from publications. The obtained results were very promising and showed that this algorithm might be very suitable for use, especially, in the continuous optimization.

KeywordBat Algorithm Optimization Self-adaptation Swarm Intelligence
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Document TypeConference paper
Corresponding AuthorIztok Fister Jr.; Simon Fong; Janez Brest; Iztok Fister
Affiliation1.University of Maribor, Faculty of Electrical Engineering and Computer Science, Smetanova 17, 2000 Maribor, Slovenia
2.University of Macau, Faculty of Science and Technology, Av. Padre Tomas Pereira, Taipa, Macau SAR
Corresponding Author AffilicationFaculty of Science and Technology
Recommended Citation
GB/T 7714
Iztok Fister Jr.,Simon Fong,Janez Brest,et al. Towards the self-adaptation of the bat algorithm[C],2014:400-406.
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