Title :
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
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;
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
DOI :
10.1109/ICMLC.2009.5212102
