Abstract
Particle swarm optimization with passive congregation (PSOPC) was a new variant by adding an attraction of passive congregation. However, the performance of PSOPC is not stable when solving the multimodal benchmarks. To overcome this shortcoming, a modified particle swarm optimization based on a Chinese archaism (PSOCA) is designed. The experimental results demonstrate much better performance of the PSOCA in solving multimodal problems than that of the PSOPC and other two variants.
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