Supervised Parallel Genetic Algorithms in Aerodynamic Optimisation

  • D. J. Doorly
  • J. Peiró


This paper describes the application of parallel genetic algorithms (coupled with CFD analysis) to problems of optimal aerodynamic or aerodynamic-structural design of wings and airfoils. The method has been implemented on a variety of parallel architectures, and results to illustrate its application are presented. A common problem with genetic algorithms (GAs) is how to maintain diversity of the gene pool and avoid premature convergence of the population. Subdivision of the population into semi-isolated subpopulations (commonly referred to as ‘demes’) not only helps significantly in this regard, but is ideally suited to implementation on parallel environments. Considerable further advantages may be obtained when some form of automated supervision is added to direct the operation of the parallel GA. A supervision strategy and its parallel implementation are also considered.


Genetic Algorithm Parallel Genetic Algorithm Airfoil Shape Airfoil Optimisation Airfoil Geometry 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Wien 1998

Authors and Affiliations

  • D. J. Doorly
    • 1
  • J. Peiró
    • 1
  1. 1.Department of AeronauticsImperial CollegeLondonUK

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