A fast annealing evolutionary algorithm for global optimization

被引:58
作者
Cai, WS [1 ]
Shao, XG
机构
[1] Univ Sci & Technol China, Dept Appl Chem, Hefei 230026, Anhui, Peoples R China
[2] Univ Sci & Technol China, Dept Chem, Hefei 230026, Anhui, Peoples R China
关键词
annealing evolutionary algorithm; global optimization; Lennard-Jones clusters;
D O I
10.1002/jcc.10029
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
By combining the aspect of population in genetic algorithms (GAs) and the simulated annealing algorithm (SAA), a novel algorithm, called fast annealing evolutionary algorithm (FAEA), is proposed. The algorithm is similar to the annealing evolutionary algorithm (AEA), and a very fast annealing technique is adopted for the annealing procedure. By an application of the algorithm to the optimization of test functions and a comparison of the algorithm with other stochastic optimization methods, it is shown that the algorithm is a highly efficient optimization method. It was also applied in optimization of Lennard-Jones clusters and compared with other methods in this study. The results indicate that the algorithm is a good tool for the energy minimization problem. (C) 2002 John Wiley Sons, Inc.
引用
收藏
页码:427 / 435
页数:9
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