遗传算法研究原子团簇

GENETIC ALGORITHM IN ATOMIC CLUSTER RESEARCH

遗传算法作为一种结构优化方法应用于研究原子团簇的结构和性质 ,具有高效和全局搜索等特点。本文扼要介绍遗传算法基本特征、优化程序和方法。重点讨论我们近年来在应用遗传算法研究碳 60分子聚集超团簇的幻数 ,金团簇有序和无序结构 ,双金属团簇的偏析效应以及过渡金属团簇电磁性质的结构关联等方面所取得的一些结果 ,说明遗传算法与传统优化方法相比确具一定优势 ,以及需要解决的问题。

Genetic algorithm is used to study structures and properties of atomic clusters as structural optimization technique,which has high efficiency and global search.In this article we give a brief introduction to characteristic method as well as program design of genetic algorithm at first.Then the stress will be devoted to our recent results on cluster research such as magic numbers of (C 60 ) N superclusters,ordered and disordered structures of medium?sized gold clusters,segregation of bimetallic clusters and structural effect of electronic and magnetic properties of transition metal clusters as a function of cluster size,etc.It indicates that genetic algorithm is really superior over conventional optimization methods in certain aspects.Finally,some problems which remain to be solved are discussed.