An improved particle swarm optimization by hybriding with JADE
2017
To overcome the weakness of particle swarm optimization (PSO), this study proposed an improvement of PSO by hybriding the adaptive differential evolution with optional external archive (JADE), named PSOJADE, to balance the global and local search capabilities. To evaluate the effectiveness of the algorithm, in the experiments, the proposed algorithm is compared with six other advanced similar techniques using 30 benchmark functions in CEC2017. The experimental results indicate that the proposed algorithm yields better solution accuracy than the other techniques on 30-D dimension.
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