DocumentCode :
2838187
Title :
Adaptive Immune Evolutionary Algorithms Based on Immune Network Regulatory Mechanism
Author :
He, Hong ; Qian, Feng
Author_Institution :
East China Univ. of Sci. & Technol., Shanghai
fYear :
2006
fDate :
15-17 Dec. 2006
Firstpage :
2456
Lastpage :
2461
Abstract :
Based on immune network regulatory mechanism, a new adaptive immune evolutionary algorithm (AIEA) is proposed to improve the performance of genetic algorithms (GA) in this paper. AIEA adopts novel selection operation according to the stimulation level of each antibody. A memory base for good antibodies is devised simultaneously to raise the convergent rapidity of the algorithm and adaptive adjusting strategy of antibody population is used for preventing the loss of the population adversity. The experiments show AIEA has better convergence performance than standard genetic algorithm and is capable of maintaining the adversity of the population and solving function optimization problems in an efficient and reliable way.
Keywords :
artificial immune systems; convergence; genetic algorithms; adaptive adjusting strategy; adaptive immune evolutionary algorithms; algorithm convergence; antibodies; antibody population; genetic algorithms; immune network regulatory mechanism; memory base; selection operation; Automation; Cloning; Computer networks; Electronic mail; Euclidean distance; Evolutionary computation; Genetic algorithms; Hamming distance; Helium; Immune system;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Technology, 2006. ICIT 2006. IEEE International Conference on
Conference_Location :
Mumbai
Print_ISBN :
1-4244-0726-5
Electronic_ISBN :
1-4244-0726-5
Type :
conf
DOI :
10.1109/ICIT.2006.372630
Filename :
4237952
Link To Document :
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