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ABCluster: the artificial bee colony algorithm for cluster global optimization
Ist Teil von
Physical chemistry chemical physics : PCCP, 2015-01, Vol.17 (37), p.24173-24181
Ort / Verlag
England
Erscheinungsjahr
2015
Link zum Volltext
Quelle
MEDLINE
Beschreibungen/Notizen
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.
Global optimization of cluster geometries is of fundamental importance in chemistry and an interesting problem in applied mathematics. We apply a swarm-intelligence based heuristic algorithm,
i.e.
the artificial bee colony algorithm to solve this problem for various kinds of clusters.