title: An unbiased population-based search for the geometry optimization of Lennard-Jones clusters: 2 < or = N < or = 372.
abstract: 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 < or = N < or = 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.
authors.affiliation: School of Information and Communication Technology, Griffith University, Gold Coast, Qld., 4215, Australia. w.pullan@griffith.edu.au
authors.forename: Wayne
authors.initials: W
authors.lastname: Pullan