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
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;
Conference_Titel :
Computer Science and Electronics Engineering (ICCSEE), 2012 International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4673-0689-8
DOI :
10.1109/ICCSEE.2012.40