A new fuzzy genetic alogorithm based on population diversity

Proceedings of IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA

Volumn 2001-January, Issue , 2001, Pages 108-112

  Wang, Kejun ^a  

^a HARBIN ENGINEERING UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; GENETIC ALGORITHMS;

COMPUTATIONAL FORMULA; CROSSOVER RATES; FUZZY - GENETIC ALGORITHMS; FUZZY CONTROLLERS; PD MEASUREMENTS; POPULATION DIVERSITY; PRE-MATURE CONVERGENCES; QUANTITATIVE RELATIONS;

ROBOTICS;

EID: 84949193368     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CIRA.2001.1013181     Document Type: Conference Paper

References (6)

1. Booker, L., Genetic Algorithms and Simulated Annealing, Los Altos, CA: Morgan Kaufmanns, 1987.
2. Mark, A., Ronneburg, F., Dynamics in A Evolving population, Parallel Problem Solving from Nature, 2, Manner, R., Manderick, B. (Editors), Elservier Science Publishers B., V., 1992.
3. Srinivas, M., Patnaik, M., Adaptive Probabilities of Crosser and Mutation in Genetic Algorithms, IEEE Trans. on SMC, vol. 24, no. 4, pp. 656-667, April, 1994.
4. Wang, P. Y., Wang, G. S., Fuzzy Logic Controlled Genetic Algorithms, IEEE Proc. on fuzzy systems, pp. 972-979, 1996.
5. Lee, M. A., Takagi, H., Dynamic Control of Genetic Algorithms using Fuzzy Logic Techniques, In Proc, Fifth International Conference on GAs, pp. 76-83 Urbana-Champaign, 1993.
6. Voigt, H. M., Fuzzy Recombination for the Breeder Genetic Algorithm, Proc. of the sixth Int. Conf. on Genetic Algorithms, pp. 104-111, San Francisco, August 1995.