An unbiased population-based search for the geometry optimization of Lennard-Jones clusters: 2 <= N <= 372

作者：Pullan W^*

来源：Journal of Computational Chemistry, 2005, 26(9): 899-906.

DOI：10.1002/jcc.20226

• global geometry optimization
• clusters
• Lennard-Jones

This article presents the results obtained using an unbiased Population Based Search (PBS) for optimizing Lennard-Jones clusters. PBS is able to repeatedly obtain all putative global minima, for Lennard-Jones clusters in the range 2 <= N <= 372, as reported in the Cambridge Cluster Database. The PBS algorithm incorporates and extends key techniques that have been developed in other Lennard-Jones optimization algorithms over the last decade. Of particular importance are the use of cut-and-paste operators, structure niching (using the cluster strain energy as a metric), two-phase local search, and a new operator, Directed Optimization, which extends the previous concept of directed mutation. In addition, PBS is able to operate in a parallel mode for optimizing larger clusters.

• 出版日期2005-7-15