作者: Zhenlun Yang , Angus Wu , Haihua Liao , Jianxin Xu
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摘要: An elitist promotion quantum-behaved particle swarm optimization (EP-QPSO) based on differential evolution operators is proposed and studied empirically in this paper. The EP-QPSO uses the procedure to perform search each particle's personal best of individually enhance global ability algorithm. A comprehensive simulation study conducted unimodal multimodal benchmark functions. Comparing with original algorithm three state-of-the-art algorithms, results indicate that has better capability faster convergence speed.