Computer Engineering and Applications ›› 2021, Vol. 57 ›› Issue (22): 92-101.DOI: 10.3778/j.issn.1002-8331.2011-0409

• Theory, Research and Development • Previous Articles     Next Articles

Piecewise Weight and Mutation Opposition-Based Learning Butterfly Optimization Algorithm

LI Shouyu, HE Qing, DU Nisuo   

  1. 1.College of Big Data & Information Engineering, Guizhou University, Guiyang 550025, China
    2.Guizhou Big Data Academy, Guizhou University, Guiyang 550025, China
  • Online:2021-11-15 Published:2021-11-16



  1. 1.贵州大学 大数据与信息工程学院,贵阳 550025
    2.贵州大学 贵州省大数据产业发展应用研究院,贵阳 550025


In order to solve the problems of the original butterfly optimization algorithm, such as local optimal solution, slow convergence speed and low searching precision, a piecewise weight and mutation opposition-based learning butterfly optimization algorithm is proposed. Firstly, the flight guidance strategy is adopted to correct the flight of butterflies in the neighborhood, reduce blind flight, and enhance the ability of the algorithm to jump out of local optimal solution. Then, the segmented weight is introduced to balance the ability of global exploration and local development, so as to realize the dynamic updating of butterfly position. Finally, the mutation opposition-based learning is used to perturb the location, increase the population diversity and improve the convergence rate of the algorithm. The optimization ability of the improved algorithm is evaluated on 9 test functions, partial CEC2014 functions and Wilcoxon rank sum test. The experimental results show that the convergence speed and optimization accuracy of the improved algorithm are greatly improved.

Key words: Butterfly Optimization Algorithm(BOA), flight guidance strategy, piecewise weight, mutation opposition-based learning, statistical test



关键词: 蝴蝶优化算法(BOA), 飞行引领策略, 分段权重, 变异反向学习, 统计检验