Abstract
Differential Evolution (DE) is an evolution algorithm that was proposed by Storn and Price in 1997, which has already succeeded in applying to solve optimization questions in a lot of fields. This paper discusses various kinds of characteristics that DE demonstrates at first, then propose an improved differential evolution algorithm (TSDE) which has three kinds of efficiently evolutionary strategies, and proves its global convergence property use the finite Markov chain theory. Through the compare result of calculation of 5 classics testing functions, it shows that TSDE has the obvious advantage in the quality of solution, adaptability, robustness etc. than original DE and DEfirDE. © 2008 Springer Berlin Heidelberg.
Cite
CITATION STYLE
He, Y., Kou, Y., & Shen, C. (2008). An improved differential evolution based on triple evolutionary strategy. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5370 LNCS, pp. 89–97). https://doi.org/10.1007/978-3-540-92137-0_10
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