为提高蝙蝠算法的寻优精度和收敛速度,提出一种融合均匀变异和高斯变异的蝙蝠优化算法.算法引入变异开关函数,该函数使所有蝙蝠个体在任何时期都有概率发生变异,使种群保持较高的多样性和活跃性.同时在算法整个寻优过程中融入均匀变异和高斯变异,两种变异机制共同协作使算法首先快速定位到全局最优解区域,随后完成局部精确搜索.仿真结果表明,改进后的算法寻优性能显著提高,具有较快的收敛速度和较高的收敛精度. In order to improve the search accuracy and convergence rate of bat algorithm, a bat algorithm based on uniform mutation and Gaussian mutation is proposed.The algorithm introduces mutation switch function, which makes all bat individuals have the mutation probability at any time, High diversity and activity.At the same time, the uniform mutation and Gaussian mutation are incorporated into the whole optimization process of the algorithm.The two mutation mechanisms work together to make the algorithm firstly locate the global optimal solution area first and then complete the local accurate search.The simulation results The results show that the improved algorithm has a significantly improved performance in search optimization, with faster convergence speed and higher convergence accuracy.