Computer Science

Computer Science ›› 2021, Vol. 48 ›› Issue (11A): 142-146.doi: 10.11896/jsjkx.201200071

• Intelligent Computing • Previous Articles     Next Articles

Optimization of Empire Competition Algorithm Based on Gauss-Cauchy Mutation

WEI Xin, FENG Feng   

  1. School of Information Engeineering,Ningxia University,Yinchuan 750021,China
  • Online:2021-11-10 Published:2021-11-12
  • About author:WEI Xin,born in 1996,postgraduate.His main research interests include improvement of intelligent algorithm.
    FENG Feng,born in 1971,Ph.D,professor.His main research interests include information system engineering and application and so on.
  • Supported by:
    Major Projects of Ningxia Key Research and Development Plan(2018BFG02003) and Postgraduate Innovation Project of Ningxia University(GIP2020091).

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Abstract: In order to solve the problems of slow convergence speed and easy to fall into local optimum in the competition process of imperial competitive algorithm (ICA),a new imperial competitive algorithm based on Gauss-Cauchy mutation (GCICA) is proposed.Gauss mutation is introduced in ICA Empire competition to speed up the convergence speed in the competition process;after the Empire perishes,the diversity is reduced and only in a small area for optimization,and Cauchy mutation is introduced to make it jump out of local optimum.By analyzing the simulation results of the algorithm with Gauss,Cauchy and Gauss-Cauchy mutation on several typical benchmark functions,the convergence speed and optimization accuracy of GCICA are improved.

Key words: Cauchy mutation, Gauss mutation, Imperial competition algorithm, Optimization algorithm

CLC Number: 

  • TP301.6
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