Performance comparison of evolutionary algorithms for airfoil design

Marcus Randall*, Tim Rawlins, Andrew Lewis, Timoleon Kipouros

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

10 Citations (Scopus)
137 Downloads (Pure)


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.

Original languageEnglish
Title of host publicationInternational conference on computational science, ICCS 2015 Computational science at the gates of nature
EditorsS Koziel, L Leifsson, M Lees, VV Krzhizhanovskaya, J Dongarra, PMA Sloot
Number of pages10
Publication statusPublished - 1 Jan 2015
Event15th Annual International Conference on Computational Science (ICCS) - Reykjavik, Reykjavik, Iceland
Duration: 1 Jun 20153 Jun 2015

Publication series

NameProcedia Computer Science
PublisherElsevier BV
ISSN (Print)1877-0509


Conference15th Annual International Conference on Computational Science (ICCS)


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