Abstract
In view of the disadvantages such as easy to fall into local optimum and slow convergence of PSO, a simplified particle swarm optimization algorithm based on improved learning factor and search method (LSSPSO) is proposed. Based on the simplified particle swarm optimization algorithm, the values of learning factor are dynamically changed by using the sine-cosine strategy, which promotes the learning ability of particle. Meanwhile, a new search method is proposed to enhance the sufficiency of particle learning. Experimental results of eight test functions show that the proposed algorithm has better comprehensive optimization performance than other six compared optimization algorithms.
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