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In this paper, a novel dynamic multi-swarm particle swarm optimizer (PSO) is introduced. Different from the existing multi-swarm PSOs and the local version of PSO, the swarms are dynamic and the swarms' size is small. The whole population is divided into many small swarms, these swarms are regrouped frequently by using various regrouping schedules and information is exchanged among the swarms. Experiments are conducted on a set of shifted rotated benchmark functions and results show its better performance when compared with some recent PSO variants.
Liang et al. (Tue,) studied this question.
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