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An Improved Differential Evolution Based on Triple Evolutionary Strategy

  • Yichao He
  • Yingzhan Kou
  • Chunpu Shen
Part of the Lecture Notes in Computer Science book series (LNCS, 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.

Keywords

Differential Evolution Global Convergence Differential Evolution Algorithm Markov Chain Theory Differential Vector 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Yichao He
    • 1
  • Yingzhan Kou
    • 2
  • Chunpu Shen
    • 3
  1. 1.School of Information EngineeringShijiazhuang University of EconomicsShijiazhuangChina
  2. 2.Computer Engineering DepartmentOrdnance Engineering CollegeShijiazhuangChina
  3. 3.College of Mathematics and Information ScienceHebei Normal UniversityShijiazhuangChina

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