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An Improved Differential Evolution Based on Triple Evolutionary Strategy

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5370))

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.

This paper is supported by the National Natural Science Foundation of China under Grant (NO. 60471022) and Key Scientific Research project of Hebei Province (NO.07216926).

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© 2008 Springer-Verlag Berlin Heidelberg

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He, Y., Kou, Y., Shen, C. (2008). An Improved Differential Evolution Based on Triple Evolutionary Strategy. In: Kang, L., Cai, Z., Yan, X., Liu, Y. (eds) Advances in Computation and Intelligence. ISICA 2008. Lecture Notes in Computer Science, vol 5370. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92137-0_10

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  • DOI: https://doi.org/10.1007/978-3-540-92137-0_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-92136-3

  • Online ISBN: 978-3-540-92137-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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