Atavistic Strategy for Genetic Algorithm
Atavistic evolutionary strategy for genetic algorithm is put forward according to the atavistic phenomena existing in the process of biological evolution, and the framework of the new strategy is given also. The effectiveness analysis of the new strategy is discussed by three characteristics of the reproduction operators. The introduction of atavistic evolutionary strategy is highly compatible with the minimum induction pattern, and increases the population diversity to a certain extent. The experimental results show that the new strategy improves the performance of genetic algorithm on convergence time and solution quality.
Keywordsgenetic algorithm atavistic evolutionary strategy atavistic operator atavistic probability premature convergence
Unable to display preview. Download preview PDF.
- 2.Xu, Z.B., Gao, Y.: Analysis and prevention of the genetic algorithm premature characteristics. Science in China, Series E 26, 364 (1996)Google Scholar
- 3.Wang, M.L., Wang, X.G., Liu, G.: Quantitative analysis and prevention of genetic algorithm premature convergence. Systems Engineering and Electronics 28, 1249–1251 (2006)Google Scholar
- 4.Fu, X.H., Kang, L.: Study of the premature convergence of genetic algorithms. Journal of Huazhong University of Science and Technology (Nature Science) 31, 53–54 (2003)Google Scholar
- 5.Zhou, H.W., Yuan, J.H., Zhang, L.S.: Improved Politics of Genetic Algorithms for Premature. Computer Engineering 33, 201–203 (2007)Google Scholar
- 6.Zhang, L., Zhang, B.: Research on the Mechanism of Genetic Algorithms. Journal of Software 11, 945–952 (2000)Google Scholar
- 7.Sultan, B.M., Mahmud, R., Sulaiman, M.N.: Reducing Premature Convergence Problem through Numbers Structuring in Genetic Algorithm. International Journal of Computer Science and Network Security 7, 215–217 (2007)Google Scholar
- 9.Fu, X.F.: An Algebraic Model for State Space of GA. Mathematics in Practice and Theory 35, 119–123 (2005)Google Scholar
- 10.Xu, Z.B., Zhang, J.S., Zheng, Y.L.: The bionics in computation intelligence: theory and algorithm. Science Press, Beijing (2003)Google Scholar