Yahya, N.M., Tokhi, M.O. and Kasdirin, H.A. (2016) A new bats echolocation-based algorithm for single objective optimisation. Evolutionary Intelligence, 9 (1). pp. 1-20. ISSN 1864-5909
Abstract
Bats sonar algorithm (BSA) as a swarm intel- ligence approach utilises the concept of echolocation of bats to find prey. However, the algorithm is unable to achieve good precision and fast convergence rate to the optimum solution. With this in mind, an adaptive bats sonar algorithm is introduced with new paradigms of real bats echolocation behaviour. The performance of the algorithm is validated through rigorous tests with several single objective optimisation benchmark test functions. The obtained results show that the proposed scheme out- performs the BSA in terms of accuracy and convergence speed and can be efficiently employed to solve engineering problems.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Author(s) 2016. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
Keywords: | Optimisation; Bats echolocation; Reciprocal altruism; Bats sonar algorithm; Adaptive bats sonar algorithm |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 21 Jul 2016 11:39 |
Last Modified: | 21 Jul 2016 11:39 |
Published Version: | http://dx.doi.org/10.1007/s12065-016-0134-5 |
Status: | Published |
Publisher: | Springer Verlag |
Refereed: | Yes |
Identification Number: | 10.1007/s12065-016-0134-5 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:101931 |