中文摘要：

为提高蝙蝠算法（bat algorithm,BA）的收敛性及求解性能,一种基于插值预测的思想可以引用到基本蝙蝠算法中,即插值蝙蝠算法（interpolated bat algorithm,IBA）,在蝙蝠正常飞行的基础上,通过蝙蝠历史位移轨迹拟合蝙蝠飞行曲线,预测蝙蝠下一个位置。通过对9个典型的测试函数进行测试实验,从解空间维度、稳定性与收敛性3个方面考虑,实验结果表明,插值蝙蝠算法与蝙蝠算法相比,具有较快的收敛速度并得到更精确的结果;插值蝙蝠算法与粒子群优化算法（particle swam optimization algorithm,PSO）进行对比,整体实验结果表明,蝙蝠算法与插值蝙蝠算法在收敛速度及精确度上比粒子群算法具有更好效果。

英文摘要：

To improve the astringency and the performance of the solution of BA（bat algorithm）,a thought based on interpolated method was introduced into the base bat algorithm,namely the interpolated bat algorithm（IBA）,with the normal flight and the history track of the bat,a flying curve was fitted to predict the next position of the bat.Considering the three aspects of dimension,stability and astringency,nine typical benchmark functions were tested.Results of simulation show that compared with the BA,IBA has faster astringency and gets more accurate results.The interpolated bat algorithm was compared with PSO（particle swarm optimization） algorithm.The overall results of the experiment show,bat algorithm and interpolation bat algorithm have better effects in astringency and accuracy than particle swarm optimization algorithm.