Title :
A Hybrid Evolutionary Algorithm Based on EDAs and Clustering Analysis
Author :
Aizeng, Cao ; Yueting, Chen ; Jun, Wei ; Jinping, Li
Author_Institution :
Jinan Univ., Jinan
Abstract :
An improved mixed evolutionary algorithm is proposed, which is based on evolutionary trend, EDAs (estimation of distribution algorithms) and clustering analysis. First, the population is classified by clustering algorithm, then for each class, partial individuals of next generation are generated by EDAs, and the rest are supplemented by combination of extrema among classes, which can overcome the premature effectively. When the individuals in some classes converge to a small field, an exhaustive local search replaces EDAs. Simulation shows the algorithm can not only improve the global searching greatly, but also overcome premature effectively.
Keywords :
evolutionary computation; pattern clustering; search problems; statistical analysis; EDA; clustering analysis; distribution algorithm estimation; exhaustive local search; hybrid evolutionary algorithm; mixed evolutionary algorithm; Algorithm design and analysis; Clustering algorithms; Electronic design automation and methodology; Evolutionary computation; Genetic algorithms; Hybrid intelligent systems; Information analysis; Information science; Pattern analysis; Pattern recognition; EDAs; Genetic algorithm; clustering analysis; extrema combination; premature;
Conference_Titel :
Control Conference, 2007. CCC 2007. Chinese
Conference_Location :
Hunan
Print_ISBN :
978-7-81124-055-9
Electronic_ISBN :
978-7-900719-22-5
DOI :
10.1109/CHICC.2006.4347236
