Title :
An Improved Immune Genetic Algorithm Based on Niche Algorithm and Its Application
Author :
Dong, Lili ; Xue, Chaogai ; Li, Guohua
Author_Institution :
Sch. of Manage. Eng., Zhengzhou Univ., Zhengzhou, China
Abstract :
In order to overcome traditional genetic algorithm (GA)\´s deficiency of slow convergence, and Niche algorithm\´s too fast convergence, this paper presents a new Improved Immune Genetic Algorithm (IIGA) based on the improved Niche algorithm. Firstly, the improved Niche algorithm, including convergence function, and "noise" chromosome, is given. Then based on the proposed flowchart of IIGA, the steps of the algorithm are introduced in detail. Finally, the IIGA is exemplified, and proved to be feasible and effective by comparing with self-adaptive Genetic Algorithm(SAGA) and traditional GA.
Keywords :
convergence; genetic algorithms; convergence function; improved immune genetic algorithm; niche algorithm; noise chromosome; Acceleration; Biological cells; Chaos; Convergence; Engineering management; Flowcharts; Genetic algorithms; Genetic engineering; Immune system; Scheduling algorithm;
Conference_Titel :
Information Engineering and Electronic Commerce (IEEC), 2010 2nd International Symposium on
Conference_Location :
Ternopil
Print_ISBN :
978-1-4244-6972-7
Electronic_ISBN :
978-1-4244-6974-1
DOI :
10.1109/IEEC.2010.5533280