计算物理 ›› 2012, Vol. 29 ›› Issue (3): 459-465.

• 论文 • 上一篇    下一篇

自适应混合遗传算法优化团簇

邢小宁, 井西利, 马毅恒, 王全志, 许耀芸   

  1. 燕山大学理学院, 河北 秦皇岛, 066004
  • 收稿日期:2011-08-08 修回日期:2011-12-02 出版日期:2012-05-25 发布日期:2012-05-25
  • 作者简介:邢小宁(1986-),女,河就秦皇岛,硕士生,从事计算匿簇结构的数值模拟研究.E-mall:xinglixin63@126.com
  • 基金资助:
    国家自然科学基金(40374048);河北自然科学基金(D20100011502)资助项目

Adaptive Hybrid Genetic Algorithm for Atomic Clusters

XING Xiaoning, JING Xili, MA Yiheng, WANG Quanzhi, XU Yaoyun   

  1. College of Science, Yanshan University, Qinhuangdao 066004, China
  • Received:2011-08-08 Revised:2011-12-02 Online:2012-05-25 Published:2012-05-25

摘要: 提出一种用于原子团簇结构优化的方法,该方法把具有全局寻优能力的自适应遗传算法与基于牛顿法思想提出的局部优化方法相结合.碳团簇的结构优化用于验证新方法的合理性,计算结果与自适应遗传算法的结果相比较,证明所提出的局部优化方法能够有效地搜索到局部极值,计算结果和混合遗传算法的结果进行对比,证明提出的自适应混合遗传算法能有效地解决"早熟"现象,并且通过对C12的四次计算,表明该算法具有一定的稳定性.

关键词: 自适应遗传算法, 牛顿法, 结构优化, 碳团簇

Abstract: We develop an optimization method for stable geometries of atomic clusters.It combines adaptive genetic algorithm,which has the ability of global optimization,with a local optimization method proposed in this paper which is based on the Newton method.Geometry optimization of carbon clusters is used to test the method.Compared with adaptive genetic algorithm,it is found that the new local optimization method can find local extremum effectively.Compared with hybrid genetic algorithm,it shows that the method can jump out of local extremes.The method presents good stability in four optimizations of C12.

Key words: adaptive genetic algorithm, Newton method, geometry optimization, carbon cluster

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