Computer Science ›› 2019, Vol. 46 ›› Issue (6A): 106-110.

• Intelligent Computing • Previous Articles     Next Articles

Differential Evolution Algorithm with Stage-based Strategy Adaption

NI Hong-jie, PENG Chun-xiang, ZHOU Xiao-gen, YU Li   

  1. College of Information Engineering,Zhejiang University of Technology,Hangzhou 310023,China
  • Online:2019-06-14 Published:2019-07-02

Abstract: To solve the problem of the selection for the mutation strategy in differential evolution algorithm,this paper proposed a differential evolution with stage-based strategy adaption.Firstly,the crowding degree of the population is measured by the average distance between each individual and the best individual,and the evolution stage is estimated.Then,the population is divided into multiple sub-populations,and a pool mutation strategy based on the coevolution of sub-populations is designed for different stages.Finally,according to the historical success information of each strategy,a suitable strategy is adaptively selected from the corresponding strategy pool to balance the exploration and exploitation.Experimental results on 12 classical test functions show that the proposed algorithm is superior to the mainstream algorithm in terms of the computational cost,success rate,quality of the solution,and scalability.

Key words: Coevolution, Differential evolution, Global optimization, Strategy self-adaption, Sub-population

CLC Number: 

  • TP391
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