Abstract: Since the convergence speed of the Firefly Algorithm (FA) is slow, and the solution accuracy of the FA is low, an improved Firefly Algorithm with Uniform local search and Variable step size (UVFA) was proposed. Firstly, uniform local search was established by the uniform design theory to accelerate convergence and to enhance exploitation ability. Secondly, search step size was dynamically tuned by using the variable step size strategy to balance exploration and exploitation. Finally, uniform local search and variable step size were fused. The results of simulation tests on twelve benchmark functions show that the objective function mean of UVFA was significantly better than FA, WSSFA (Wise Step Strategy for Firefly Algorithm), VSSFA (Variable Step Size Firefly Algorithm) and Uniform local search Firefly Algorithm (UFA), and the time complexity was obviously reduced. UVFA is good at solving low dimensional and high dimensional problems, and has good robustness.

Key words: Firefly Algorithm (FA), uniform design, uniform local search, global optimization, variable step size

摘要： 针对萤火虫算法（FA）收敛速度慢和求解精度不高的问题，提出一种基于均匀局部搜索和可变步长策略的萤火虫优化算法（UVFA）。首先，根据均匀设计理论建立局部搜索算子，对FA的搜索过程进行改进，以提升算法的局部开采能力和收敛速度；其次，利用可变步长策略，动态地调整算法搜索步长，以平衡全局和局部的勘探能力和开采能力；最后将均匀局部搜索算子和可变步长进行融合。通过对12个标准测试函数进行仿真实验，结果表明，UVFA的目标函数均值均明显优于FA、明智步长策略的萤火虫算法（WSSFA）、可变步长萤火虫算法（VSSFA）和基于均匀局部搜索的萤火虫优化算法（UFA），并且时间复杂度明显降低，并且在低维和高维问题中均显示出了较好的质量，具有良好的鲁棒性。

关键词: 萤火虫算法, 均匀设计, 均匀局部搜索, 全局优化, 可变步长