Title :
Fuzzy logic controlled genetic algorithms
Author :
Wang, P.Y. ; Wang, G.S. ; Song, Y.H. ; Johns, A.T.
Author_Institution :
Electr. Power Res. Inst., Beijing, China
Abstract :
The fuzzy logic controlled genetic algorithm (FCGA) is presented, in which two fuzzy logic controllers are implemented to adaptively adjust the crossover rate and mutation rate during the optimization process. The FCGA is implemented in TC++ on a PC486 and tested by a power economic dispatch problem. The comparison between the FCGA and the conventional genetic algorithm (CGAs) is performed, which demonstrates that the FCGA has much better performance
Keywords :
controllers; fuzzy control; fuzzy logic; genetic algorithms; PC486; TC++; conventional genetic algorithm; crossover rate; fuzzy logic controlled genetic algorithms; fuzzy logic controllers; mutation rate; optimization process; power economic dispatch problem; Automatic control; Biological cells; Constraint optimization; Cost function; Decoding; Equations; Fuzzy logic; Genetic algorithms; Genetic mutations; Random number generation;
Conference_Titel :
Fuzzy Systems, 1996., Proceedings of the Fifth IEEE International Conference on
Conference_Location :
New Orleans, LA
Print_ISBN :
0-7803-3645-3
DOI :
10.1109/FUZZY.1996.552310
