Dynamic Multi-Swarm Particle Swarm Optimizer with Sub-regional Harmony Search

In this paper, the dynamic multi-swarm particle swarm optimizer (DMS-PSO) and a sub-regional harmony search (SHS) are hybridized to obtain DMS-PSO-SHS. A Modified multi-trajectory search (MTS) algorithm is also applied frequently on several selected solutions. Effective diversity maintaining properties of the dynamic multiple swarms in the DMS-PSO without crossover operation and strong exploitative properties of the HS with multi-parent crossover operation strengthen the overall search behavior of the proposed DMS-PSO-SHS. The whole PSO population is divided into a large number sub-swarms which is also the individual HS population. These sub-swarms are regrouped frequently by using various regrouping schedules and information is exchanged among the particles in the whole swarm. Therefore, different from the existing multi-swarm PSOs or local versions of PSO, our sub-swarms are dynamic and its size is small which is also appropriate to be the population of the harmony search. In addition, an external memory of selected past solutions is used to enhance the diversity of the swarm. The DMS-PSO-SHS is employed to solve the 20 numerical optimization problems for the CEC'2010 Special Session and Competition on Large Scale Global Optimization and competitive results are presented.