Journal of Frontiers of Computer Science and Technology ›› 2021, Vol. 15 ›› Issue (6): 1155-1164.DOI: 10.3778/j.issn.1673-9418.2010032

• Theory and Algorithm • Previous Articles    

Improved Sparrow Algorithm Combining Cauchy Mutation and Opposition-Based Learning

MAO Qinghua, ZHANG Qiang   

  1. School of Economics and Management, Yanshan University, Qinhuangdao, Hebei 066004, China
  • Online:2021-06-01 Published:2021-06-03



  1. 燕山大学 经济管理学院,河北 秦皇岛 066004


Aiming at the problem that the population diversity of basic sparrow search algorithm decreases and it is easy to fall into local extremum in the late iteration, an improved sparrow search algorithm combining Cauchy variation and reverse learning (ISSA) is proposed. Firstly, this paper uses a Sin chaotic initialization population with an unlimited number of mapping folds to lay the foundation for global optimization. Secondly, this paper introduces the previous generation global optimal solution into the discoverer location-update method to enhance the sufficiency of global search. At the same time, the adaptive weight is added to coordinate the ability of local mining and global exploration, and the convergence speed is accelerated. Then, the Cauchy mutation operator and the opposition-based learning strategy are combined to perform disturbance mutation to generate new solutions at the optimal solution position, and the algorithm??s ability to jump out of local space is enhanced. Finally, this algorithm is compared with 3 basic algorithms and 2 improved sparrow algorithms. Simulation and Wilcoxon rank and inspection are performed on 8 benchmark test functions. The optimization performance of ISSA is assessed, and time complexity analysis of ISSA is carried out. The results show that ISSA has faster convergence rate and higher precision than the other 5 algorithms. And the overall optimization capabilities are improved.

Key words: sparrow search algorithm, Sin chaos, adaptive, Cauchy variation, opposition-based learning



关键词: 麻雀搜索算法, Sin混沌, 自适应, 柯西变异, 反向学习