How to select optimal control parameters for genetic algorithms

Author

Yang, Qi-Wen ; Jiang, Jing-Ping ; Chen, Guo

Author_Institution

Coll. of Electr. Eng., Zhejiang Univ., China

Volume

1

fYear

2000

fDate

2000

Firstpage

37

Abstract

In order to enhance the optimization efficiency, it´s important for genetic algorithms (GAs) to select optimal control parameters. But the theory behind parameter setting for a GA gives little guidance for their selection. We have being selected the control parameters for GAs only by trials so far. In this paper, we discuss the function of genetic operators and present the conception of natality of schema (NS). We put forward an approach to estimating the optimal ranges of the control parameters for GAs by utilizing the NS. The approach is proven effectively by a genetic algorithm based on Boolean operators (GABO) which is proposed in this paper

Keywords

Boolean algebra; genetic algorithms; Boolean operators; genetic algorithms; genetic operators; natality of schema; optimal control parameters; optimization efficiency; Educational institutions; Evolution (biology); Genetic algorithms; Genetic mutations; Heuristic algorithms; Machine learning algorithms; Optimal control; Optimization methods; Space technology; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Electronics, 2000. ISIE 2000. Proceedings of the 2000 IEEE International Symposium on

Conference_Location

Cholula, Puebla

Print_ISBN

0-7803-6606-9

Type

conf

DOI

10.1109/ISIE.2000.930482

Filename

930482