DocumentCode :
175718
Title :
Hybrid quantum crossover based immune clonal algorithm and its application
Author :
Hongwei Dai ; Yu Yang ; Cunhua Li
Author_Institution :
Jiangsu Inst. of Marine Resources, Lianyungang, China
fYear :
2014
fDate :
19-21 Aug. 2014
Firstpage :
390
Lastpage :
395
Abstract :
In order to overcome the premature convergence problem of clonal selection algorithm (CSA), a hybrid quantum crossover is proposed to improve the performance of CSA. The hybrid crossover is composed of two crossovers and well balance the exploration and exploitation search during immune maturation process. The effectiveness of the new crossover based CSA is evaluated on a class of traveling salesman problems (TSP). Simulation results demonstrate the performance of the proposed algorithm.
Keywords :
biology; travelling salesman problems; CSA; TSP; bioinspired computing; clonal selection algorithm; hybrid quantum crossover; immune clonal algorithm; immune maturation process; premature convergence problem; traveling salesman problems; Cities and towns; Convergence; Immune system; Optimization; Simulation; Sociology; Statistics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation (ICNC), 2014 10th International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4799-5150-5
Type :
conf
DOI :
10.1109/ICNC.2014.6975867
Filename :
6975867
Link To Document :
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