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物理学报. 2005, 54(11): 5281-5287.
doi: 10.7498/aps.54.5281.
基于克隆选择的混合遗传算法在碳纳米管结构优化中的研究
- 收稿日期: 2004-11-30
- 修回日期: 2005-03-28
- 刊出日期: 2005-11-20
English Abstract
Study of structure optimization of carbon nanotubes using hybrid genetic algorithm based on clonal selection principle
- Received Date:
30 November 2004
- Accepted Date:
28 March 2005
- Published Online:
20 November 2005
Abstract: Focusing on the problem of carbon nanotube structure optimization by molecule dynamics simulation, a novel algorithm is proposed which combines the genetic algorithm with simulated annealing and the clone select algorithm.Test results of five typical functions show that this algorithm has high stability and gives good global optimization. Applied to structure optimization of carbon nanotubes, it can accelerate the process of energy optimization and improve the quality of structure optimization.The simulation results show that the optimizing time increases linearly with the number of atoms.The time of structure optimization is reduced one order of maguitucle compared with the conjugate gradient methods.
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