Paper Title:
The Design of Adaptive Immune Vaccine Algorithm
  Abstract

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)
Chapter
Intelligent Optimization Design
Edited by
Jian Gao
Pages
1094-1098
DOI
10.4028/www.scientific.net/AMR.308-310.1094
Citation
G. L. Yuan, Y. G. Xue, Q. J. Liang, "The Design of Adaptive Immune Vaccine Algorithm", Advanced Materials Research, Vols. 308-310, pp. 1094-1098, 2011
Online since
August 2011
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Price
$32.00
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