DocumentCode
1899424
Title
Immune-Difference Algorithm
Author
Fu, Xuan ; Liu, Hao ; Fan, Yaoqun ; Zhao, Xinchao
Author_Institution
Sch. of Sci., Beijing Univ. of Posts & Telecommun., Beijing, China
Volume
2
fYear
2012
fDate
23-25 March 2012
Firstpage
406
Lastpage
409
Abstract
This paper introduces difference mutation idea for diversified search to elitist search-based immune optimization algorithm for function optimization. The idea of difference mutation is merged into the process of clonal selection and hupermutation algorithm, so that the new solutions have the tendency to get close to the global optimal solution. The introduction of differential algorithm idea greatly accelerates the convergence speed and makes the search algorithm produces better performance under a fixed number of steps. In short, the performance of the immune algorithm is greatly improved by introduction of differential algorithm.
Keywords
artificial immune systems; convergence; search problems; clonal selection; convergence speed; difference mutation; differential algorithm; elitist search-based immune optimization algorithm; function optimization; global optimal solution; hupermutation algorithm; immune-difference algorithm; search algorithm; Arrays; Cloning; Convergence; Educational institutions; Immune system; Optimization; Software algorithms; Clonal Selection; Difference algorithm; Hypermutation; Immune algorithm;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Electronics Engineering (ICCSEE), 2012 International Conference on
Conference_Location
Hangzhou
Print_ISBN
978-1-4673-0689-8
Type
conf
DOI
10.1109/ICCSEE.2012.40
Filename
6188050
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