In this paper, the dynamic multi-swarm particle swarm optimizer (DMS-PSO) is improved by hybridizing
it with the harmony search (HS) algorithm and the resulting algorithm is abbreviated as DMS-PSO-HS.
We present a novel approach to merge the HS algorithm into each sub-swarm of the DMS-PSO. Combining
the exploration capabilities of the DMS-PSO and the stochastic exploitation of the HS, the DMSPSO-HS
is developed. The whole DMS-PSO population is divided into a large number of small and
dynamic sub-swarms which are also individual HS populations. These sub-swarms are regrouped
frequently and information is exchanged among the particles in the whole swarm. The DMS-PSO-HS
demonstrates improved on multimodal and composition test problems when compared with the
DMS-PSO and the HS.