TY - GEN
T1 - Particle Swarm Optimization with Hybrid Ring Topology for Multimodal Optimization Problems
AU - Chen, Zong-Gan
AU - Zhan, Zhi-Hui
AU - Liu, Dong
AU - Kwong, Sam
AU - Zhang, Jun
PY - 2020/10
Y1 - 2020/10
N2 - Multimodal optimization problems (MMOPs) require the algorithm to locate multiple global optima and also achieve a certain accuracy on the found optima. When applying particle swarm optimization (PSO) to solve MMOPs, a fixed population communication topology may not be sufficient to handle these two requirements simultaneously. In this paper, a novel PSO with hybrid ring topology, termed HRTPSO, is proposed for MMOPs. In the early evolutionary process of HRTPSO, a sparse topology is constructed to enhance the population diversity to help locate multiple optima, while in the later evolutionary process of HRTPSO, the population communication topology is switched to a relatively dense topology for improving the convergence efficiency on the found optima. The switch of topology is controlled by a threshold and its effect is also analyzed in this paper. Experimental results on the 20 multimodal functions in CEC'2013 benchmark set show that HRTPSO has better performance than the other six multimodal optimization algorithms.
AB - Multimodal optimization problems (MMOPs) require the algorithm to locate multiple global optima and also achieve a certain accuracy on the found optima. When applying particle swarm optimization (PSO) to solve MMOPs, a fixed population communication topology may not be sufficient to handle these two requirements simultaneously. In this paper, a novel PSO with hybrid ring topology, termed HRTPSO, is proposed for MMOPs. In the early evolutionary process of HRTPSO, a sparse topology is constructed to enhance the population diversity to help locate multiple optima, while in the later evolutionary process of HRTPSO, the population communication topology is switched to a relatively dense topology for improving the convergence efficiency on the found optima. The switch of topology is controlled by a threshold and its effect is also analyzed in this paper. Experimental results on the 20 multimodal functions in CEC'2013 benchmark set show that HRTPSO has better performance than the other six multimodal optimization algorithms.
KW - hybrid ring topology
KW - multimodal optimization problems
KW - Particle swarm optimization
UR - http://www.scopus.com/inward/record.url?scp=85098885382&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85098885382&origin=recordpage
U2 - 10.1109/SMC42975.2020.9282962
DO - 10.1109/SMC42975.2020.9282962
M3 - RGC 32 - Refereed conference paper (with host publication)
T3 - IEEE Transactions on Systems, Man, and Cybernetics: Systems
SP - 2044
EP - 2049
BT - 2020 IEEE International Conference on Systems, Man, and Cybernetics
PB - IEEE
T2 - 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2020)
Y2 - 11 October 2020 through 14 October 2020
ER -