Global geometry optimization of clusters using a growth strategy optimized by a genetic algorithm
chem-ph
2009-10-28 v1 Chemical Physics
Abstract
A new strategy for global geometry optimization of clusters is presented. Important features are a restriction of search space to favorable nearest-neighbor distance ranges, a suitable cluster growth representation with diminished correlations, and easy transferability of the results to larger clusters. The strengths and possible limitations of the method are demonstrated for Si10 using an empirical potential.
Keywords
Cite
@article{arxiv.chem-ph/9505002,
title = {Global geometry optimization of clusters using a growth strategy optimized by a genetic algorithm},
author = {Bernd Hartke},
journal= {arXiv preprint arXiv:chem-ph/9505002},
year = {2009}
}
Comments
accepted by Chem.Phys.Letters; 10 pages text, plus 3 pages for Title, abstract, and figure caption; figures 1a and 1b