Chaotic Mutation Bee Evolution Algorithm

Article Preview

Abstract:

In order to make full use of chaotic mutation genetic algorithm and the chaotic mutation and bee evolution algorithm, the characteristics of the two algorithms, and the combination of chaotic mutation bee evolution algorithm is proposed. The algorithm in bee evolution process, to adapt to the value of group of smaller portions of the variation of individuals to chaos; to adapt to the value of group of large part of the individual, to the best individual as the center, change crossover operation, each generation is the best individual immune evolutionary iterative calculation. Thus, as the iteration, the algorithm not only fast convergence, and can also by a higher accuracy by the global optimal solution.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 482-484)

Pages:

1636-1639

Citation:

Online since:

February 2012

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2012 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Srinivas M , Patnaik L M. Genetic Algorithms: A Survey [J]. Computer,1994,27 (6):17-26

Google Scholar

[2] Bennet t C H, Shor P. Quantum Information Theory[J]. IEEE Trans on Information Theory , 1998, 44 (6) :2724-2742

DOI: 10.1109/18.720553

Google Scholar

[3] Narayanan A. Moore M, Quantum-inspired genetic algorithm [A]. Procof IEEE International Conference on Evolutionary Computation [C]. Piscataway: IEEE Press, 1996, 61-66.

Google Scholar

[4] Yang S Y, Jiao L C. The Quantum Evolutionary Programming [A]. 15th Int Conf on Computational Intelligence and Multimedia Applications[C]. IEEE P ress, 2003: 362-367

Google Scholar

[5] Zhang G X, Gu Y J , Hu L Z, et al. A Novel Genetic Algorithm and Its Application to Digital Filter Design[A ]. Pro con IEEE Intelligent Transportation Systems[C]. IEEE Press, 2003, 2: 1600-1605

DOI: 10.1109/itsc.2003.1252754

Google Scholar

[6] Chen H, Zhang J S. Chaos Updating Rotated Gates Quantum inspired Genetic Algorithm [A]. IEEE Pro con Communications, Circuits and Systems [C]. Chengdu: UESTC Press, 2004: 1108-1112.

DOI: 10.1109/icccas.2004.1346370

Google Scholar

[7] SHANG Yun-wei; QIU Yu-huang. Influence of fitness sharing on the selection probability of genetic algorithm [J]. Control and Decision,2003,18 (6):708-711(In Chinese)

Google Scholar

[8] CHEN Hui; ZHANG Jia-shu; ZHANG Chao. Real-coded Chaotic Quantum-inspired Genetic Algorithm[J]. Control and Decision,2005,20(11):1300-1303

Google Scholar

[9] ZHAO Xiao-li; LI Zuo-yong; DING Jing. Application of Improved Quantum Genetic Algorithm to the Evaluation of Sustainable Utilization of Regional Water Resources [J]. Journal of Natural Resources,2007,22(6):980-985

Google Scholar