Performance comparison of evolutionary algorithms for airfoil design

Different evolutionary algorithms, by their very nature, will have different search trajectory characteristics. Understanding these particularly for real world problems gives researchers and practitioners valuable insights into potential problem domains for the various algorithms, as well as an unde...

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Published in:Procedia Computer Science
Main Authors: Randall, M, Rawlins, T, Lewis, A, Kipouros, T
Format: Conference Object
Language:English
Published: Elsevier 2015
Subjects:
Online Access:http://hdl.handle.net/10072/104584
https://doi.org/10.1016/j.procs.2015.05.384
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spelling ftgriffithuniv:oai:research-repository.griffith.edu.au:10072/104584 2024-06-23T07:54:01+00:00 Performance comparison of evolutionary algorithms for airfoil design Randall, M Rawlins, T Lewis, A Kipouros, T 2015-06-01 to 2015-06-03 Reykjavik, Iceland 2015 http://hdl.handle.net/10072/104584 https://doi.org/10.1016/j.procs.2015.05.384 English eng Elsevier Procedia Computer Science ICCS 2015 http://hdl.handle.net/10072/104584 1877-0509 doi:10.1016/j.procs.2015.05.384 http://creativecommons.org/licenses/by-nc-nd/4.0/ © 2015 The Authors. Published by Elsevier B.V. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) License (https://creativecommons.org/licenses/by-nc-nd/4.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, providing that the work is properly cited. You may not alter, transform, or build upon this work. open access Optimisation Information and computing sciences Aerodynamics (excl. hypersonic aerodynamics) Conference output 2015 ftgriffithuniv https://doi.org/10.1016/j.procs.2015.05.384 2024-05-29T00:10:31Z Different evolutionary algorithms, by their very nature, will have different search trajectory characteristics. Understanding these particularly for real world problems gives researchers and practitioners valuable insights into potential problem domains for the various algorithms, as well as an understanding for potential hybridisation. In this study, we examine three evolutionary techniques, namely, multi-objective particle swarm optimisation, extremal optimisation and tabu search. A problem that is to design optimal cross sectional areas of airfoils that maximise lift and minimise drag, is used. The comparison analyses actual parameter values, rather than just objective function values and computational costs. It reveals that the three algorithms had distinctive search patterns, and favoured different regions during exploration of the design space. Griffith Health, School of Human Services and Social Work Full Text Conference Object Iceland Griffith University: Griffith Research Online Griffith ENVELOPE(-155.500,-155.500,-85.883,-85.883) Procedia Computer Science 51 2267 2276
institution Open Polar
collection Griffith University: Griffith Research Online
op_collection_id ftgriffithuniv
language English
topic Optimisation
Information and computing sciences
Aerodynamics (excl. hypersonic aerodynamics)
spellingShingle Optimisation
Information and computing sciences
Aerodynamics (excl. hypersonic aerodynamics)
Randall, M
Rawlins, T
Lewis, A
Kipouros, T
Performance comparison of evolutionary algorithms for airfoil design
topic_facet Optimisation
Information and computing sciences
Aerodynamics (excl. hypersonic aerodynamics)
description Different evolutionary algorithms, by their very nature, will have different search trajectory characteristics. Understanding these particularly for real world problems gives researchers and practitioners valuable insights into potential problem domains for the various algorithms, as well as an understanding for potential hybridisation. In this study, we examine three evolutionary techniques, namely, multi-objective particle swarm optimisation, extremal optimisation and tabu search. A problem that is to design optimal cross sectional areas of airfoils that maximise lift and minimise drag, is used. The comparison analyses actual parameter values, rather than just objective function values and computational costs. It reveals that the three algorithms had distinctive search patterns, and favoured different regions during exploration of the design space. Griffith Health, School of Human Services and Social Work Full Text
format Conference Object
author Randall, M
Rawlins, T
Lewis, A
Kipouros, T
author_facet Randall, M
Rawlins, T
Lewis, A
Kipouros, T
author_sort Randall, M
title Performance comparison of evolutionary algorithms for airfoil design
title_short Performance comparison of evolutionary algorithms for airfoil design
title_full Performance comparison of evolutionary algorithms for airfoil design
title_fullStr Performance comparison of evolutionary algorithms for airfoil design
title_full_unstemmed Performance comparison of evolutionary algorithms for airfoil design
title_sort performance comparison of evolutionary algorithms for airfoil design
publisher Elsevier
publishDate 2015
url http://hdl.handle.net/10072/104584
https://doi.org/10.1016/j.procs.2015.05.384
op_coverage 2015-06-01 to 2015-06-03
Reykjavik, Iceland
long_lat ENVELOPE(-155.500,-155.500,-85.883,-85.883)
geographic Griffith
geographic_facet Griffith
genre Iceland
genre_facet Iceland
op_relation Procedia Computer Science
ICCS 2015
http://hdl.handle.net/10072/104584
1877-0509
doi:10.1016/j.procs.2015.05.384
op_rights http://creativecommons.org/licenses/by-nc-nd/4.0/
© 2015 The Authors. Published by Elsevier B.V. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) License (https://creativecommons.org/licenses/by-nc-nd/4.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, providing that the work is properly cited. You may not alter, transform, or build upon this work.
open access
op_doi https://doi.org/10.1016/j.procs.2015.05.384
container_title Procedia Computer Science
container_volume 51
container_start_page 2267
op_container_end_page 2276
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