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.
|Title of host publication||Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics|
|Publication status||Published - Oct 2020|
Bibliographical noteThis work was supported in part by the Key-Area Research and Development of Guangdong Province under Grant 2020B010166002, the National Key Research and Development Program of China under Grant 2019YFB2102102, the Outstanding Youth Science Foundation under Grant 61822602, the National Natural Science Foundations of China under Grant 61772207 and Grant 61873097, the Guangdong Natural Science Foundation Research Team under Grant 2018B030312003 and 2018B050502006, the Ministry of Science and ICT through the National Research Foundation of Korea (NRF-2019H1D3A2A01101977), and the Hong Kong GRF-RGC General Research Fund (9042489) under Grant CityU 11206317.
- hybrid ring topology
- multimodal optimization problems
- Particle swarm optimization