Differential Evolution Algorithm Based on Beta Distribution
ZHANG Zhe
WANG Lifang
Abstract：To address the drawbacks of poor solution accuracy,the tendency to fall into local optimum and slow convergence of the differential evolution algorithm,a differential evolution algorithm BetaDE based on the beta distribution is proposed.BetaDE takes advantage of the beta distribution's distribution in the 0～1 interval and uses the adaptive generation of the learning factor F in the differential evolution algorithm to determine the value of the individual adaptation to the values of the control parameters,thus balancing the diversity of the algorithm as well as the convergence performance,while avoiding falling into local optima.Simulation experiments are carried out on standard test functions,which show that BetaDE outperforms other algorithms in terms of solution ac-curacy and convergence speed.
Keywords：differential evolution algorithmBeta distributioncontrol parametersadaptive
Publication Date：2025-11-20
Online Publishing Date：2026-01-28(First online date of this platform, not the publication date of the document)
Pages：5( 3001-3005 )