Abstract:When traditional particle swarm optimization algorithms deal with highly complex, ultra-high-dimensional problems, traditional particle learning strategies can only provide little help. In this paper, a particle swarm optimization algorithm with a hybrid variation domain dimension learning strategy is proposed, which uses the domain dimension average of the current particle dimension to generate guiding particles. At the same time, an improved inertia weight is also used, which effectively avoids the algorithm… Show more
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