融合正弦余弦的蝙蝠算法

Bat algorithm fused with sine cosine

蝙蝠算法(Bat Algorithm,BA)是一种新颖的随机型搜索优化算法,针对蝙蝠算法收敛速度慢、寻优精度低的不足,提出了一种融合正弦余弦的蝙蝠算法(SCABA),即在算法迭代后期,引入正弦余弦操作来更新当前蝙蝠个体的位置,从而避免算法陷入局部最优,增强算法的全局寻优能力。通过6个标准测试函数对改进算法、MFBA和基本BA进行测试比较,仿真结果表明,改进算法是可行有效的,相比于基本BA算法,其收敛精度和鲁棒性有了很大程度地提高。

Bat Algorithm（BA） is a novel random search optimization algorithm.In order to overcome the shortcomings of slowconvergence speed and poor optimization accuracy of bat algorithm,bat algorithm（SCABA） based on sine cosine is proposed,In the later iteration,the sine cosine operation is introduced to update the current individual position of the bat,thereby enhancing the diversity of the population,avoiding the algorithm getting into the local optimum and enhancing the global optimization ability of the algorithm.The improved algorithm,MFBA and basic BA are tested by six standard test functions.The simulating results showthat the improved algorithm is feasible and effective.Compared with the basic BA algorithm,the convergence precision and robustness have been greatly improved.