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Differential evolution (DE) algorithm is widely used for solving real-parameter optimization problems due to its simplicity and efficiency. However the canonical DE is easy to suffer from the premature convergence. To further improve the performance of the DE, a differential evolution algorithm with dual preferred learning mutation (DPLDE) is proposed. Dual preferred learning mutation simultaneously...
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