Publication Type:

Journal Article


International Journal of Computers and Applications, Volume 34, Number 2, p.135-144 (2012)



Comparative performance analysis, Differential Evolution, Evolutionary algorithms, Global optimization, Global optimization problems, Mutation strategy, Objective function values, Successful runs, Test functions


In this paper, we extend the dynamicity of differential evolution (DE) proposed for DE/rand/1/bin and DE/best/1/bin to five more variants DE/rand/2, DE/best/2, DE/current-to-rand/1, DE/current-to-best/1 and DE/rand-to-best/1. We present an empirical, comparative performance, analysis of 14 variants of DE and dynamic differential evolution (DDE) algorithms (7 variants with two crossovers - binomial and exponential) to solve unconstrained global optimization problems. The aim of this paper is to identify competitive DE and DDE variants which perform well on ifferent problems, and to compare the performance of DDE variants with DE variants. The performance of 14 variants of DE and DDE are analyzed by implementing them on 14 test functions. The analysis (done based on mean objective function value, probability of convergence and success performance) shows the superiority of DDE variants and identifies the competitive DE and DDE variants.


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Cite this Research Publication

G. Jeyakumar and Velayutham, C. N. S., “Differential evolution and dynamic differential evolution variants - An empirical comparative performance analysis”, International Journal of Computers and Applications, vol. 34, pp. 135-144, 2012.