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 additio...

• Type: Conference
• Year: 2010
• Where: CEC
• Authors: Shi-Zheng Zhao, Ponnuthurai Nagaratnam Suganthan, Swagatam Das
• Keywords: Artificial Intelligence, CEC 2010, Crossover Operation, Harmony Search, Particle Swarm Optimizer