A hybrid strategy combining differential evolution with simplex gradient
Xiaowei Zhang, Sanyang Liu · 2012
Differential Evolution has been made great achievements in various fields such as computational sciences, engineering optimization, and operations management. However, the choice of the mutation strategy is important to the performance of DE. In order to enhance the performance of DE, we present a hybrid strategy combining differential evolution with simplex gradient. The hybrid strategy can maintain the appropriate balance between exploration and exploitation. The comparisons of numerical experiments among the proposed algorithm with the hybrid strategy and four other algorithms with the different setting strategies are done, which show that the proposed algorithm outperforms the other compared algorithms.