Breeder Genetic Algorithms represent a class of random optimisation techniques gleaned from the science of population genetics, which have proved their ability to solve hard optimisation problems with continuous parameters. In this paper we test a parallel version of this technique against a sequential Breeder Genetic Algorithm on a typical inverse design problem in Aerodynamics, the problem of an aerofoil geometry recover starting from a target pressure distribution. Our results show that Parallel Breeder Genetic Algorithms are well suited for applications in Aerodynamics.
Investigating a Parallel Breeder Genetic Algorithm on the Inverse Aerodynamic Design
I De Falco;E Tarantino
1996
Abstract
Breeder Genetic Algorithms represent a class of random optimisation techniques gleaned from the science of population genetics, which have proved their ability to solve hard optimisation problems with continuous parameters. In this paper we test a parallel version of this technique against a sequential Breeder Genetic Algorithm on a typical inverse design problem in Aerodynamics, the problem of an aerofoil geometry recover starting from a target pressure distribution. Our results show that Parallel Breeder Genetic Algorithms are well suited for applications in Aerodynamics.File in questo prodotto:
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