DocumentCode :
460799
Title :
Adaptive Parallel Immune Evolutionary Strategy
Author :
Bo, Cheng ; Zhenyu, Guo
Author_Institution :
Res. & Dev. Center of Electr. Vehicle, Xi´´an Jiaotong Univ.
Volume :
1
fYear :
2006
fDate :
Nov. 2006
Firstpage :
304
Lastpage :
307
Abstract :
Based on clonal selection theory, an adaptive parallel immune evolutionary strategy (PIES) is presented. On the grounds of antigen-antibody affinity, the original antibody population can be divided into two subgroups. Correspondingly, two operators, elitist clonal operator (ECO) and super mutation operator (SMO), are proposed. The former is adopted to improve the local search ability while the latter is used to maintain the population diversity. Thus, population evolution can be actualized by concurrently operating ECO and SMO, which can enhance searching efficiency of the algorithm. Experimental results show that PIES is of high efficiency and can effectively prevent premature convergence. Therefore, it can be employed to solve complicated optimization problems
Keywords :
evolutionary computation; adaptive parallel immune evolutionary strategy; antigen-antibody affinity; clonal selection theory; elitist clonal operator; local search ability; population diversity; super mutation operator; Cells (biology); Cloning; Convergence; Evolution (biology); Evolutionary computation; Extraterrestrial phenomena; Genetic mutations; Immune system; Land vehicles; Shape;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Security, 2006 International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
1-4244-0605-6
Electronic_ISBN :
1-4244-0605-6
Type :
conf
DOI :
10.1109/ICCIAS.2006.294143
Filename :
4072096
Link To Document :
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