Breeder genetic algorithms for airfoil design optimisation

Author

De Falco, I. ; Del Balio, R. ; Cioppa, A. Della ; Tarantino, E.

Author_Institution

Res. Inst. on Parallel Inf. Syst., Nat. Res. Council of Italy, Naples, Italy

fYear

1996

Firstpage

71

Lastpage

75

Abstract

In this paper a version of genetic algorithms, the breeder genetic algorithms, suitable for continuous parameter optimisation, has been applied and compared to a classical discrete genetic algorithm. The application concerns a typical optimisation problem in aerodynamics, the problem of determining the coordinates of an airfoil given a surface pressure distribution. Our results have shown that the breeder genetic algorithms work better than classical discrete-coded genetic algorithms in this field

Keywords

CAD; aerodynamics; aerospace computing; computational geometry; curve fitting; genetic algorithms; inverse problems; aerodynamics; airfoil coordinates; airfoil design optimisation; breeder genetic algorithms; computational geometry; continuous parameter optimisation; curve fitting; discrete genetic algorithm; discrete-coded genetic algorithms; inverse problems; surface pressure distribution; Aerodynamics; Algorithm design and analysis; Automotive components; Councils; Design optimization; Electronic switching systems; Genetic algorithms; Humans; Information systems; Inverse problems;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation, 1996., Proceedings of IEEE International Conference on

Conference_Location

Nagoya

Print_ISBN

0-7803-2902-3

Type

conf

DOI

10.1109/ICEC.1996.542336

Filename

542336