Computer Science

Computer Science ›› 2019, Vol. 46 ›› Issue (6A): 89-92.

• Intelligent Computing • Previous Articles     Next Articles

Bat Optimization Algorithm Based on Dynamically Adaptive Weight and Cauchy Mutation

ZHAO Qing-jie1, LI Jie1, YU Jun-yang1,2, JI Hong-yuan1   

  1. School of Software,Henan University,Kaifeng,Henan 475004,China1;
    State Key Laboratory of Network and Exchange Technology,Beijing University of Posts and Telecommunications,Beijing 100876,China2
  • Online:2019-06-14 Published:2019-07-02

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Abstract: In order to speed up the convergence of bat algorithm and improve the accuracy of optimization,this paper proposed a bat optimization algorithm based on dynamic adaptive weight and Cauchy mutation.The algorithm adds dynamic adaptive weight to the speed formula and dynamically adjusts the size of the adaptive weight to speed up the convergence of the algorithm.In addition,the Cauchy inverse cumulative distribution function method can effectively improve the global search ability of bat algorithm and avoid falling into local optimum.The simulation results of 12 typical test functions show that the improved algorithm has better performance,faster convergence speed and higher optimization accuracy.

Key words: Bat algorithm, Cauchy mutation, Convergence contrast, Dynamically adaptive weight

CLC Number: 

  • TP301.6
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