Single-parent evolution algorithm and the optimization of Si clusters

We describe a novel method for the structural optimization of molecular sys tems. Similar to genetic algorithms (GA), our approach involves an evolving population in which new members are formed by cutting and pasting operatio ns on existing members. Unlike previous GA's, however, the population in ea ch generation has a single parent only. This scheme has been used to optimi ze Si clusters with 13-23 atoms. We have found a number of new isomers that are lower in energy than any previously reported and have properties in mu ch better agreement with experimental data.