Antenna design using animal migration optimisation algorithm
- Author(s): Ezgi Deniz Ülker 1 and Sadık Ülker 2
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View affiliations
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Affiliations:
1:
Department of Computer Engineering , European University of Lefke , Lefke Mersin-10 , Turkey ;
2: Department of Electrical and Electronics Engineering , European University of Lefke , Lefke Mersin-10 , Turkey
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Affiliations:
1:
Department of Computer Engineering , European University of Lefke , Lefke Mersin-10 , Turkey ;
- Source:
Volume 2016, Issue 8,
August
2016,
p.
298 – 301
DOI: 10.1049/joe.2016.0123 , Online ISSN 2051-3305
This is an open access article published by the IET under the Creative Commons Attribution-NonCommercial-NoDerivs License (http://creativecommons.org/licenses/by-nc-nd/3.0/)
Received
22/04/2016,
Accepted
23/05/2016,
Published
26/05/2016
The use of swarm intelligence algorithms for solving complex optimisation problems is an interesting area since they can produce remarkable results. The animal migration optimisation (AMO) algorithm is one of the swarm intelligence algorithms which is derived from the migration behaviour of animals. The implementation of AMO algorithm for complex array optimisation problems is given. The experimental studies show that the AMO algorithm produces high-quality results and it is capable to overcome strong local optimum points by using its attributes. Also, it has few number of steps which are quite easy to implement. The AMO can be suggested as a powerful algorithm for optimisation problems including complex array designs when the high solution quality is desired.
Inspec keywords: design engineering; optimisation; dipole antennas; antenna feeds; swarm intelligence
Other keywords: swarm intelligence algorithms; animal migration optimisation algorithm; AMO algorithm; migration behaviour; antenna design; variable length centre fed dipole; complex array optimisation problems
Subjects: Single antennas; Antenna accessories; Optimisation techniques
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