基于遗传算法的全局优化及在团簇结构搜索中的应用

Global Optimization based on Genetic Algorithm and Its Application in Cluster Structure Search

遗传算法是研究复杂体系特性时经常采用的一种高效的全局优化方法.以开发出的程序为基础,介绍了遗传算法的基本特征、操作步骤、技术细节及在团簇结构优化中的运用.通过在富勒烯和铋团簇两类代表性团簇结构优化问题中的具体应用,所得结果与已有的理论和实验数据符合较好,印证了所提出的操作方案的有效性、高效性和通用性.

Genetic algorithm was an efficient global optimization method to explore the properties of complex systems. In this article,based on our recently developed programme,we describe the basic philosophy,typical procedure and technique details of genetic algorithm for global structural search of clusters. As examples of the practical applications of the genetic algorithm for clusters,the lowest energy structures of fullerene and Bi clusters have been determined. Our results agree well with available experimental and theoretical data,indicating genetic algorithm is very valid and efficient,and capable of dealing with many problems.