Global geometry optimization of clusters using genetic algorithms

A genetic algorithm is used to find the global minimum energy structure for Si 4 on an empirical potential energy surface. Given a suitable encoding of the cluster geometry, and an exponential scaling of the potential energy values to obtain a fitness function, the genetic algorithm can successfully optimize all degrees of freedom. With the number of potential energy function evaluations as a measure, the genetic algorithm is more economical than either a set of traditional, local minimizations or a molecular dynamics simulated annealing approach