Advertisement
Published in:
2005 | OriginalPaper | Chapter
Clonal Selection with Immune Dominance and Anergy Based Multiobjective Optimization
Authors : Licheng Jiao, Maoguo Gong, Ronghua Shang, Haifeng Du, Bin Lu
Published in: Evolutionary Multi-Criterion Optimization
Publisher: Springer Berlin Heidelberg
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
Based on the concept of Immunodominance and Antibody Clonal Selection Theory, we propose a new artificial immune system algorithm, Immune Dominance Clonal Multiobjective Algorithm (IDCMA). The influences of main parameters are analyzed empirically. The simulation comparisons among IDCMA, the Random-Weight Genetic Algorithm and the Strength Pareto Evolutionary Algorithm show that when low-dimensional multiobjective problems are concerned, IDCMA has the best performance in metrics such as Spacing and Coverage of Two Sets.