An adaptive immune optimization algorithm with dynamic lattice searching operation for fast optimization of atomic clusters

作者：Wu Xia^*; Wu Genhua

来源：Chemical Physics, 2014, 440: 94-98.

DOI：10.1016/j.chemphys.2014.06.002

• Global optimization
• Immune optimization algorithm
• Dynamic lattice searching
• Lennard-Jones clusters
• Silver clusters

Geometrical optimization of atomic clusters is performed by a development of adaptive immune optimization algorithm (AIOA) with dynamic lattice searching (DLS) operation (AIOA-DLS method). By a cycle of construction and searching of the dynamic lattice (DL), DLS algorithm rapidly makes the clusters more regular and greatly reduces the potential energy. DLS can thus be used as an operation acting on the new individuals after mutation operation in AIOA to improve the performance of the AIOA. The AIOA-DLS method combines the merit of evolutionary algorithm and idea of dynamic lattice. The performance of the proposed method is investigated in the optimization of Lennard-Jones clusters within 250 atoms and silver clusters described by many-body Gupta potential within 150 atoms. Results reported in the literature are reproduced, and the motif of Ag-61 cluster is found to be stacking-fault face-centered cubic, whose energy is lower than that of previously obtained icosahedron.

• 出版日期2014-8-31
• 单位安庆师范大学