Fuzzy genetic algorithms based on fuzzy number coding on [0, 1] and its application

Author

Wang, Shu-tian ; Li, Zi-fang ; Zhang, Zhi-jun ; Jin, Chen-xia

Author_Institution

Dept. of Basic Sci., Hebei Inst. of Ind. Technol., Shijiazhuang, China

Volume

5

fYear

2009

fDate

12-15 July 2009

Firstpage

2564

Lastpage

2569

Abstract

An improved genetic algorithm for fuzzy programming problems with triangular fuzzy variables is proposed in this paper. The decentralization degree of fuzzy numbers is defined, and the way of coding triangular fuzzy number on [0, 1] is built. So we can limit the type of fuzzy numbers, increase the convergence property of algorithm, and make the fuzzy information processing more reasonable. Based on the structure characteristics of optimization variables, the crossover operation was replaced by linear recombination, and a compound mutation operation to triangular fuzzy numbers is given. The effectiveness and usefulness are discussed through an example in the end.

Keywords

fuzzy set theory; genetic algorithms; compound mutation operation; fuzzy genetic algorithm; fuzzy information processing; fuzzy number coding; fuzzy programming; optimization variable; triangular fuzzy number; triangular fuzzy variable; Chemical industry; Chemical technology; Convergence; Cybernetics; Design optimization; Genetic algorithms; Genetic mutations; Image coding; Information processing; Machine learning; Compound mutation; Decentralization degree; Fuzzy optimization; Genetic algorithms;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2009 International Conference on

Conference_Location

Baoding

Print_ISBN

978-1-4244-3702-3

Electronic_ISBN

978-1-4244-3703-0

Type

conf

DOI

10.1109/ICMLC.2009.5212102

Filename

5212102