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- Title
The study of genetic information flux network properties in genetic algorithms.
- Authors
Wu, Zhengping; Xu, Qiong; Ni, Gaosheng; Yu, Gaoming
- Abstract
In this paper, an empirical analysis is done on the information flux network (IFN) statistical properties of genetic algorithms (GA) and the results suggest that the node degree distribution of IFN is scale-free when there is at least some selection pressure, and it has two branches as node degree is small. Increasing crossover, decreasing the mutation rate or decreasing the selective pressure will increase the average node degree, thus leading to the decrease of scaling exponent. These studies will be helpful in understanding the combination and distribution of excellent gene segments of the population in GA evolving, and will be useful in devising an efficient GA.
- Subjects
GENETIC algorithms; EMPIRICAL research; INFORMATION theory; DISTRIBUTION (Probability theory); GENE regulatory networks
- Publication
International Journal of Modern Physics C: Computational Physics & Physical Computation, 2015, Vol 26, Issue 7, p-1
- ISSN
0129-1831
- Publication type
Article
- DOI
10.1142/S012918311550076X