Sub-population policies for a parallel multiobjective genetic algorithm with applications to wing design

Author

Quagliarella, D. ; Vicini, A.

Author_Institution

Centro Italiano Ricerche Aerospaziali, Capua, Italy

Volume

4

fYear

1998

fDate

11-14 Oct 1998

Firstpage

3142

Abstract

A parallel multi-objective genetic algorithm is presented. The population selection and mating phase is kept distinct from the population fitness evaluation loop, that is implemented in parallel. The population can be logically split in sub-populations the number of which does not depend on the number of processors available for computation. Different sub-population topologies and migration rates among sub-populations can be used. Applications are illustrated both for single and multi-objective mathematical test cases, and aerodynamic transonic wing design

Keywords

CAD; aerospace computing; genetic algorithms; parallel algorithms; aerodynamic transonic wing design; mating; parallel multiobjective genetic algorithm; population fitness evaluation loop; population selection; sub-population policies; wing design; Aerodynamics; Aerospace testing; Algorithm design and analysis; Constraint optimization; Cost function; Design optimization; Genetic algorithms; Random number generation; Switches; Topology;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man, and Cybernetics, 1998. 1998 IEEE International Conference on

Conference_Location

San Diego, CA

ISSN

1062-922X

Print_ISBN

0-7803-4778-1

Type

conf

DOI

10.1109/ICSMC.1998.726485

Filename

726485