Distributed adaptive search method for Genetic Algorithm controlled by fuzzy reasoning

Author

Li, Qiang ; Maeda, Yoichiro

Author_Institution

Dept. of Syst. Design Eng., Univ. of Fukui, Fukui

fYear

2008

fDate

1-6 June 2008

Firstpage

2022

Lastpage

2027

Abstract

In this paper, we proposed FASPGA based on diversity measure (DM-FASPGA) and FASPGA based on evolution history (EH-FASPGA) as the improvement method of fuzzy adaptive search method for parallel genetic algorithm (FASPGA). In DM-FASPGA, genetic parameters is tuning by fuzzy rule based on diversity of sub-population. Many kinds of diversity measure parameters are imported into the fuzzy rule. And in EH-FASPGA, we imported the evolution history information for improving the accuracy to estimate the evolution degree. Simulation results are also further presented to show the effectiveness and performance of method we proposed in this paper.

Keywords

fuzzy reasoning; genetic algorithms; knowledge based systems; distributed adaptive search method; diversity measure; evolution history; fuzzy adaptive search method for parallel genetic algorithm; fuzzy reasoning; Adaptive control; Design engineering; Fuzzy reasoning; Genetic algorithms; Genetic mutations; History; Learning; Multiagent systems; Programmable control; Search methods;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems, 2008. FUZZ-IEEE 2008. (IEEE World Congress on Computational Intelligence). IEEE International Conference on

Conference_Location

Hong Kong

ISSN

1098-7584

Print_ISBN

978-1-4244-1818-3

Electronic_ISBN

1098-7584

Type

conf

DOI

10.1109/FUZZY.2008.4630647

Filename

4630647