中文摘要：

为了进一步提高基本花粉授粉算法的性能,提出了一种改进的花粉授粉算法（EFPA）.该算法在演化过程中以一定的概率利用一般反向学习策略对当前种群作一般反向变换,从而生成一般反向变换种群,然后将一般反向变换种群与当前种群同时进行竞争,选择出优秀的个体进入下一代种群.在演化计算领域中广泛使用的基准测试函数上,将提出算法与基本花粉授粉算法进行了比较实验,实验结果表明提出算法能够有效地提高基本花粉授粉算法的性能.

英文摘要：

In order to improve the performance of the traditional flower pollination algorithm, an enhanced flower pollination algorithm （EFPA） is proposed in this paper. The generalized reverse learning strategy is used with a certain probability to convert the current population into a generalized reverse population. Then, the converted population is competed with the current population to select the excellent individuals for the next population. The experiments were conducted on a set of classical benchmark test functions, which are widely used in the evolutionary computation community. The comparison results between EFPA and the traditional FPA indicate that the proposed flower pollination algorithm can enhance the performance of the traditional FPA.