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Article title FEATURES OF USE OF FUZZY GENETIC ALGORITHMS FOR THE DECISION OF PROBLEMS OF OPTIMISATION AND CONTROL
Authors L.A. Gladkov, N.V. Gladkova
Section SECTION III. ARTIFICIAL INTELLECT AND INDISTINCT SYSTEMS
Month, Year 04, 2009 @en
Index UDC 519.712.2
DOI
Abstract In article the basic aspects of application of fuzzy genetic algorithms for the decision of problems of optimization and control are considered. The generalized structure of the fuzzy logic controller is resulted and the basic idea of its application is described. The basic directions and problems of creation of fuzzy genetic algorithms are in detail considered. The basic components of the organization and process of interaction of genetic algorithm and the fuzzy logic controller are described.

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Keywords Fuzzy genetic algorithm; fuzzy logic controller; fuzzification; defuzzification.
References 1. Herrera F., Lozano M. Fuzzy Genetic Algorithms: Issues and Models. – Source unknown.
2. Herrera F., Lozano M. Fuzzy Adaptive Genetic Algorithms: design, taxonomy, and future directions // Soft Computing 7(2003), Springer-Verlag, 2003. – P. 545-562.
3. Hongbo Liu, Zhanguo Xu, Ajith Abraham. Hybrid Fuzzy-Genetic Algorithm Approach for Crew Grouping. – Source unknown.
4. Herrera F., Lozano M. Adaptation of genetic algorithm parameters based on fuzzy logic controllers. In: F. Herrera, J. L. Verdegay (eds.) Genetic Algorithms and Soft Computing, Physica-Verlag, Heidelberg, 1996. – P. 95-124.
5. Michalewicz Z. Genetic Algorithms + Data Structures = Evolution Programs // New York: Springer-Verlag, 1992.
6. Lozano M., Herrera F., Krasnogor N., Molina D. Real-Coded Memetic Algorithms with Crossover Hill-Climbing. // Evolutionary Computation № 12(3), Massachusetts Institute of Technology, 2004. – P. 273-302.
7. Deb K., Joshi D., Anand A. Real-Coded Evolutionary Algorithms with Parent-Centric Recombination. Kanpur Genetic Algorithms Laboratory (KanGAL), Kanpur, PIN 208 016, India. KanGAL Report No. 2001003.
8. Гладков Л.А. Алгоритм выделения ядер в нечетких графах на основе моделирования эволюции // IX национальная конференция по искусственному интеллекту с международным участием КИИ’2004. Труды конференции. – М.: Физматлит, 2004. – С. 346-355.
9. Herrera F., Lozano M., Moraga C. Hierarchical Distributed Genetic Algorithms. // Parallel Problem Solving from Nature // International Journal of of Intelligent Systems, vol. 14, 1999. – P. 1099-1121.

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