小型微型计算机系统 Journal of Chinese Computer Systems ISSN 1000-1220,CN 21-1106/TP 合自适应惯性权重和柯西变异 的秃鹰搜索算法（CBES）。首先使用 Tent 混沌映射初始化种群，保留了种群的多样性；其次，引入自适应惯性权重，加快 算法的收敛速度，增强算法的局部开发能力；最后将柯西变异算子整合到当前全局最优位置进行变异更新，提高算法陷入 局部最优的能力。通过 12 个单模态、多模态基准测试函数对 CBES、BES、FPA、MFO、PSO 五种算法进行实验对比，实验结 果表明了改进后的算法在收敛速度和精度方面均得到了提升。同时将该算法应用到实际工程中，验证了算法的扩展性和适 用性。 关键词：秃鹰搜索算法；Tent 混沌映射；自适应惯性权重；柯西变异 中图分类号： 文献标识： A Bald Eagle Search Algorithm Combining Adaptive Inertial Weight and Cauchy Variation Ding Rong1，Gao Jian-ling 2，Zhang Qian2 （College of Big Data and Information Engineering, Guizhou University, Guiyang 550025, China） Abstract: Since the basic bald eagle search algorithm has the defects of slow convergence speed and easy to fall into local optimum, a bald eagle search (CBES) combining adaptive inertial weight and Cauchy variation is proposed. Firstly, use Tent chaotic map to initialize the population to preserve the diversity of the population; secondly, introduce adaptive inertial weights to speed up the convergence speed of the algorithm and enhance the local development capabilities of
