The Design of Adaptive Immune Vaccine Algorithm

Abstract:

Article Preview

Aiming at disadvantages of Genetic Algorithm (GA) and learning from the immune system theory, this paper introduces immune memory cell of immune theory, vaccine extraction and vaccination operator based on immune theory, and adaptive probability crossover and mutation operator to GA, to improve the optimization ability and search efficiency of GA, and proposes Adaptive Immune Vaccine Algorithm (AIVA). Then proves the convergence of the algorithm, gives the composition mechanisms of the key operators, and verifies the role of each operator. Finally, four test functions have been optimized using GA, AIGA and AIVA. The experimental results show that AIVA effectively overcomes the GA Defects, greatly prevents the degradation of population, and has perfect convergence stability and excellent global optimization capability.

Info:

Periodical:

Advanced Materials Research (Volumes 308-310)

Edited by:

Jian Gao

Pages:

1094-1098

DOI:

10.4028/www.scientific.net/AMR.308-310.1094

Citation:

G. L. Yuan et al., "The Design of Adaptive Immune Vaccine Algorithm", Advanced Materials Research, Vols. 308-310, pp. 1094-1098, 2011

Online since:

August 2011

Export:

Price:

$35.00

In order to see related information, you need to Login.

In order to see related information, you need to Login.