中文摘要：

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.

英文摘要：

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.