Jump to main content
Jump to site search

Issue 37, 2015
Previous Article Next Article

ABCluster: the artificial bee colony algorithm for cluster global optimization

Author affiliations

Abstract

Global optimization of cluster geometries is of fundamental importance in chemistry and an interesting problem in applied mathematics. In this work, we introduce a relatively new swarm intelligence algorithm, i.e. the artificial bee colony (ABC) algorithm proposed in 2005, to this field. It is inspired by the foraging behavior of a bee colony, and only three parameters are needed to control it. We applied it to several potential functions of quite different nature, i.e., the Coulomb–Born–Mayer, Lennard-Jones, Morse, Z and Gupta potentials. The benchmarks reveal that for long-ranged potentials the ABC algorithm is very efficient in locating the global minimum, while for short-ranged ones it is sometimes trapped into a local minimum funnel on a potential energy surface of large clusters. We have released an efficient, user-friendly, and free program “ABCluster” to realize the ABC algorithm. It is a black-box program for non-experts as well as experts and might become a useful tool for chemists to study clusters.

Graphical abstract: ABCluster: the artificial bee colony algorithm for cluster global optimization

Back to tab navigation

Publication details

The article was received on 12 Jul 2015, accepted on 18 Aug 2015 and first published on 19 Aug 2015


Article type: Paper
DOI: 10.1039/C5CP04060D
Author version
available:
Download author version (PDF)
Citation: Phys. Chem. Chem. Phys., 2015,17, 24173-24181
  •   Request permissions

    ABCluster: the artificial bee colony algorithm for cluster global optimization

    J. Zhang and M. Dolg, Phys. Chem. Chem. Phys., 2015, 17, 24173
    DOI: 10.1039/C5CP04060D

Search articles by author

Spotlight

Advertisements