Computer Engineering and Applications ›› 2021, Vol. 57 ›› Issue (24): 74-82.DOI: 10.3778/j.issn.1002-8331.2101-0161

• Theory, Research and Development • Previous Articles     Next Articles

Mixed Strategy Improved Sparrow Search Algorithm

ZHANG Weikang, LIU Sheng, REN Chunhui   

  1. School of Management, Shanghai University of Engineering Science, Shanghai 201620, China
  • Online:2021-12-15 Published:2021-12-13



  1. 上海工程技术大学 管理学院,上海 201620


Aiming at the shortcomings of the sparrow search algorithm in the iterations of population diversity reduction, easy to fall into local optimality and slow convergence speed, a Mixed Strategy improved Sparrow Search Algorithm(MSSSA) is proposed. Circle map is used to initialize the individual positions of sparrows to increase the diversity of the initial population. Combining the butterfly optimization algorithm the location update method of the discoverer is improved to enhance global exploration ability of the algorithm. The dimensional-by-dimensional mutation method is used to perturb the individual position and improve the algorithm’s ability to jump out of the local optimum. In the simulation experiment, it compares with 4 basic algorithms and 5 improved algorithms based on 10 benchmark functions and performs Wilcoxon rank sum test. The results show that the proposed algorithm has better convergence and solution accuracy, global optimization ability has been greatly improved.

Key words: sparrow search algorithm, butterfly optimization algorithm, dimensional-by-dimensional mutation strategy, Wilcoxon rank sum test



关键词: 麻雀搜索算法, 蝴蝶优化算法, 逐维变异策略, Wilcoxon秩和检验