DocumentCode :
2697177
Title :
A novel niche genetic algorithm with local search ability
Author :
Gu, Jun-hua ; Li, Na-Na ; TAN, QING ; WEI, WEI
Author_Institution :
Hebei Univ. of Technol., Tianjin
fYear :
2007
fDate :
25-28 Sept. 2007
Firstpage :
4606
Lastpage :
4609
Abstract :
The insufficiency of local search and slow convergence in later generations are two main disadvantages of niche genetic algorithm (NGA). In this paper, we propose an improved novel niche genetic algorithm with local search ability. Depending on the number of iteration, the new algorithm adopts the mechanism of crossover operator and mutation operator in niche population instead of between different niches to make the searching more effective. This new method is used in Shubert function optimization and experimental results show its superiority compared with GA and NGA.
Keywords :
genetic algorithms; search problems; Shubert function optimization; crossover operator; local search ability; mutation operator; niche genetic algorithm; Computer science; Evolutionary computation; Genetic algorithms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 2007. CEC 2007. IEEE Congress on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-1339-3
Electronic_ISBN :
978-1-4244-1340-9
Type :
conf
DOI :
10.1109/CEC.2007.4425075
Filename :
4425075
Link To Document :
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