Foraging on the potential energy surface: a swarm intelligence-based optimizer for molecular geometry

Abstract

We present a stochastic, swarm intelligence-based optimization algorithm for the prediction of global minima on potential energy surfaces of molecular clusterstructures. Our optimization approach is a modification of the artificial bee colony (ABC) algorithm which is inspired by the foraging behavior of honey bees. We apply our modified ABC algorithm to the problem of global geometryoptimization of molecular clusterstructures and show its performance for clusters with 2–57 particles and different interatomic interaction potentials.