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Volume 18 Issue 6
Nov.  1996
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Zhang Liangjie, Mao Zhihong, Li Yanda. MATHEMATICAL ANALYSIS OF MUTATION OPERATOR AND ITS IMPROVED STRATEGY IN GENETIC ALGORITHMS[J]. Journal of Electronics & Information Technology, 1996, 18(6): 590-595.
Citation: Zhang Liangjie, Mao Zhihong, Li Yanda. MATHEMATICAL ANALYSIS OF MUTATION OPERATOR AND ITS IMPROVED STRATEGY IN GENETIC ALGORITHMS[J]. Journal of Electronics & Information Technology, 1996, 18(6): 590-595.

MATHEMATICAL ANALYSIS OF MUTATION OPERATOR AND ITS IMPROVED STRATEGY IN GENETIC ALGORITHMS

  • Received Date: 1995-04-05
  • Rev Recd Date: 1995-07-05
  • Publish Date: 1996-11-19
  • This paper analyzes the optimization problem of mutation probability (Pm) in genetic algorithms by applying the definition of i-bit improved sub-space. Then fuzzy reasoning technique is adopted to determine the optimal mutation probability in different conditions. The superior convergence property of the new method is evaluated by applying it to two simulation examples.
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  • Rudolph G. IEEE Trans. on NN, 1994, NN-5(1): 96-101.[2]Holland J H. Adaptation in Natural and Artificial Systems, ANN Arbor: The Univ. of Michigan Press, 1975.[3]陈根社,陈新梅.信息与控制,1994,23(4): 215-222.[4]Janson D J, Frenzel J F. IEEE Expert, 1993, 8(5): 26-33.[5]Yasumasa I, Hiroaki K. IEICE Tans. Fundamentals, 1994, E77-A(4): 731-735.[6]Tomoharu N.Takeshi A[J].IEICE Trans. Information System.1993, E76-D(6):689-697[7]Zhang Liangjie, Mao Zhihong, Li Yanda. An Improved Genetic Algorithm Based on Combinative Theory Fuzzy Reasoning and its Applications, International Conference on Neural Information Processing, Korea: 1994, 180-185.[8]Hung S L, Adeli H. IEEE Trans on NN, 1994, NN-5(6): 900-909.[9]Grefenstette J J. IEEE Tans. on SMC, 1986, SMC-16(1): 122-128.[10]Goldberg D E. Genetic Algorithms in Search, Optimization and Learning. Addison Wesley Publishing Company, 1989, Chapter 4 and Chapter 5.
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