一种新的双策略进化果蝇优化算法

标准果蝇优化算法(fruit fly optimization algorithm, FOA)在迭代寻优的过程中,整个果蝇群体只向最优个体靠近,这导致算法极易陷入局部最优,从而引起早熟收敛的问题。针对该问题,提出一种新的双策略进化果蝇优化算法(a novel double strategies evolutionary fruit fly optimization algorithm, DSEFOA)。提出的一种新的群体分割策略,将果蝇群体动态地划分为精英子群和普通子群;对于精英子群,引入混沌变量引导果蝇个体在其附近搜索食物,优化其局部搜索能力;对于普通子群,引入权重因子改进标准FOA的随机搜索方式,执行全局搜索,加快收敛速度。DSEFOA算法针对不同进化水平的果蝇个体采用不同的策略更新进化,充分地提升了整个群体的寻优搜索能力。8个测试函数的仿真试验结果表明, DSEFOA算法有比标准FOA算法更好的优化性能。

A fast fractal image compression algorithm based on K-mean clustering optimization

Range and domain blocks are clustered by using K-mean clustering method,and range blocks search domain blocks in the same category,which can shorten encoding time significantly.The encoding speed of our method is about 5 times faster than that of the classical Jacquin's algorithm,and the quality of the decoding images can be retained as well when the compression ratio is fixed.We also tested some other fast encoding schemes based on variance,and the experimental results show that our algorithms are superior to them.