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Optimisation of airfoils using parallel genetic algorithms

  • D J Doorly
  • J Peiró
  • T Kuan
  • J-P Oesterle
Design Methods
Part of the Lecture Notes in Physics book series (LNP, volume 490)

Abstract

This paper describes a parallel genetic algorithm which is linked to CFD analysis for the design of optimal 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 (or 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 a network of workstations.

Keywords

Genetic Algorithm Flow Solver Parallel Genetic Algorithm Airfoil Design Airfoil Optimisation 
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 1997

Authors and Affiliations

  • D J Doorly
    • 1
  • J Peiró
    • 1
  • T Kuan
    • 1
  • J-P Oesterle
    • 1
  1. 1.Aeronautics DepartmentImperial CollegeLondonUK

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