doi: 10.4304/jsw.6.3.436-443
An Improved Immune Genetic Algorithm for the Optimization of Enterprise Information System based on Time Property
- 1 Department of Management Engineering, Zhengzhou University, Zhengzhou, 450001, China
- 2 School of Information Engineering, Zhengzhou University, Zhengzhou, 450001, China
Abstract
In order to optimize enterprise information system’s structure and improve its performance, this paper deals with the structure optimization problem based on an improved immune genetic algorithm (IIGA). First, a new immune genetic algorithm (IGA) is proposed, i.e., IIGA, which can overcome traditional genetic algorithm (GA)’s deficiency of slow convergence. In the new IGA, Niche algorithm is used to accelerate convergence speed, and measures such as convergence function, and “noise” chromosome are proposed to avoid Niche algorithm’s deficiency of premature convergence. Then the structure and time property of enterprise information system (EIS) are discussed. And then optimization model of EIS structure is given. Finally, the IIGA and its application in EIS structure optimization are exemplified, and by comparing with self-adaptive Genetic Algorithm (SAGA) and traditional GA, the results verified IIGA’s better convergence speed and optimization ability.
Keywords
- Niche Algorithm
- Improved Genetic Algori
How to Cite
Chaogai Xue, Lili Dong, and Guohua Li, "An Improved Immune Genetic Algorithm for the Optimization of Enterprise Information System based on Time Property," Journal of Software, vol. 6, no. 3, pp. 436-443, 2011. https://doi.org/ 10.4304/jsw.6.3.436-443
Copyright & License
Copyright © 2011 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).