DocumentCode :
2914814
Title :
Nearest neighbor evolutionary algorithm for constrained optimization problem
Author :
Yu, Zhiwen ; Wang, Dingwen ; Wong, Hau-San
Author_Institution :
Dept. of Comput. Sci., City Univ. of Hong Kong, Hong Kong
fYear :
2008
fDate :
1-6 June 2008
Firstpage :
2335
Lastpage :
2342
Abstract :
Although there exist a lot of approaches to solve constrained optimization problem, few of them makes use of the knowledge obtained in the searching process. In the paper, a new algorithm called nearest neighbor evolutionary algorithm (NNE) is proposed to solve the constrained optimization problem. NNE not only performs global search and local search in the searching process, but also considers the knowledge obtained in the searching process. NNE also avail itself of the elitist strategy and keeps the best individuals for the next generation. The results in the experiments show that NNE not only achieves good performance in a lot of constrained optimization problems, but also outperforms most of state-of-art approaches in most of constrained optimization problems, such as ASCHEA and SEMS.
Keywords :
evolutionary computation; optimisation; search problems; constrained optimization problem; global search; local search; nearest neighbor evolutionary algorithm; searching process; simple multimembered evolutionary strategy; Algorithm design and analysis; Bioinformatics; Constraint optimization; Evolutionary computation; Genetic algorithms; Genetic mutations; Genetic programming; Nearest neighbor searches; Robustness; Samarium;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-1822-0
Electronic_ISBN :
978-1-4244-1823-7
Type :
conf
DOI :
10.1109/CEC.2008.4631109
Filename :
4631109
Link To Document :
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