%0 Journal Article
%T Study of structure optimization of carbon nanotubes using hybrid genetic algorithm based on clonal selection principle<br>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
%A Bao Wen-Xing
%A Zhu Chang-Chun
%A Cui Wan-Zhao
%A <br>保文星
%A 朱长纯
%A 崔万照
%J 物理学报
%D 2005
%I 
%X 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.
%K molecular dynamics
%K carbon nanotube
%K energy optimization
%K genetic algorithm
%K clone select algorithm<br>分子动力学，
%K 碳纳米管，
%K 能量优化，
%K 遗传算法，
%K 克隆选择算法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=6E709DC38FA1D09A4B578DD0906875B5B44D4D294832BB8E&cid=47EA7CFDDEBB28E0&jid=29DF2CB55EF687E7EFA80DFD4B978260&aid=9DD23071D850C74A&yid=2DD7160C83D0ACED&vid=318E4CC20AED4940&iid=708DD6B15D2464E8&sid=52D2DE4F7E22F92F&eid=051328AF7C349D67&journal_id=1000-3290&journal_name=物理学报&referenced_num=2&reference_num=17