模拟退火
元优化
计算机科学
共轭梯度法
理论(学习稳定性)
全局优化
碳纳米管
遗传算法
最优化问题
算法
优化算法
分子动力学
数学优化
材料科学
数学
纳米技术
物理
机器学习
量子力学
作者
Wenxing Bao,Zhu Chang-Chun,Wanzhao Cui
出处
期刊:Chinese Physics
[Science Press]
日期:2005-01-01
卷期号:54 (11): 5281-5281
被引量:2
摘要
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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