Computer Science ›› 2015, Vol. 42 ›› Issue (Z6): 52-56.

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Dynamic Adaptive Differential Evolution Algorithm

LI Zhang-wei, ZHOU Xiao-gen and ZHANG Gui-jun   

  • Online:2018-11-14 Published:2018-11-14

Abstract: To solve the problems of convergence speed,computational cost and reliability caused by the choice of parame-ters and strategies,a dynamic adaptive differential evolution algorithm was proposed in this paper incorporating the abstract convexity theory.Firstly,an underestimate relaxed model of the objective function is built by constructing the supporting hyperplanes for the individuals of the population.Then,the underestimate values of the trial individuals that generated by the strategies in the strategies pool can be obtained from the underestimate relaxed model.So the parameters and strategies can adjust adaptively according to the underestimate and the evolutionary experience before.In addition,the underestimate also can be used to guide the update process.Finally,the underestimate supporting hyperplanes are updated according to the result of evolutionary.Numerical experiment results of the six benchmark problems verify the effectiveness of the proposed algorithm.

Key words: Differential evolution,Self-adaption,Abstract convex,Underestimate,Global optimization

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