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.
Yonggang ChenLixiang LiHaipeng PengJinghua XiaoQingtao Wu
Jing LiangPonnuthurai Nagaratnam Suganthan
Shi-Zheng ZhaoPonnuthurai Nagaratnam SuganthanQuan-Ke PanM. Fatih Tasgetiren
Xia XuYinggan TangJunpeng LiChangchun HuaXinping Guan
Jiawei LuJian ZhangJianan Sheng