Optimization method for metal nanometer cluster structure

The invention discloses an optimization method for a metal nanometer cluster structure. Through the combination of a coordinate update formula and a stochastic learning operator in a PSO (Particle Swarm Optimization) algorithm, the speed and the coordinate of the metal nanometer cluster are updated, a Quasi-Newton algorithm is used for carrying out local optimization on the updated metal nanometer cluster, and an optimal metal nanometer cluster is obtained through fitness value comparison. The method is high in accuracy and rate of convergence. 本发明公开种金属纳米团簇结构优化方法，通过PSO算法中坐标更新公式与随机学习算子的结合来更新金属纳米团簇的速度和坐标，使用拟牛顿算法对更新后的金属纳米团簇进行局部优化，通过适应度值比较得到最优的金属纳米团簇。本发明具有较高的精确度和收敛速度。