A genetic algorithm with adaptable parameters

Author

Quagliarella, D. ; Vicini, A.

Author_Institution

Centro Italiano Ricerche Aerosp., Capua, Italy

Volume

3

fYear

1999

fDate

6/21/1905 12:00:00 AM

Firstpage

598

Abstract

An approach to the self-adaptation of the parameters of a genetic algorithm to the optimization problem is described. The characterizing feature of the system presented is the structure of the evolving individuals, that are more similar to cells rather than to isolated genes with the introduction of a program chromosome besides the chromosome of the optimization problem variables. The basic scheme of the evolutionary optimizer is a multiple objective genetic algorithm based on the introduction of the dominance criteria in the selection mechanism. Some preliminary results are presented on a multimodal single-objective test function and the directions of future work are outlined

Keywords

genetic algorithms; adaptable parameters; dominance criteria; evolutionary optimizer; evolving individuals; multimodal single-objective test function; multiple objective genetic algorithm; optimization problem; program chromosome; selection mechanism; self-adaptation; Algorithm design and analysis; Biological cells; Cells (biology); Computer aided instruction; Decoding; Genetic algorithms; Genetic mutations; Robustness; Springs; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man, and Cybernetics, 1999. IEEE SMC '99 Conference Proceedings. 1999 IEEE International Conference on

Conference_Location

Tokyo

ISSN

1062-922X

Print_ISBN

0-7803-5731-0

Type

conf

DOI

10.1109/ICSMC.1999.823280

Filename

823280