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UEAS: A Novel United Evolutionary Algorithm Scheme

  • Fei Gao
  • Hengqing Tong
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4234)

Abstract

How to detect global optimums of the complex function is of vital importance in diverse scientific fields. Though stochastic optimization strategies simulating evolution process are proved to be valuable tools, the balance between exploitation and exploration of which is difficult to be maintained. In this paper, some established techniques to improve the performance of evolutionary computation are discussed firstly, such as uniform design, deflection and stretching the objective function, and space contraction. Then a novel scheme of evolutionary algorithms is proposed to solving the optimization problems through adding evolution operations to the searching space contracted regularly with these techniques. A typical evolution algorithm differential evolution is chosen to exhibit the new scheme’s performance and the experiments done to minimize the benchmark nonlinear optimization problems and to detect nonlinear map’s unstable periodic points show the put approach is very robust.

Keywords

Particle Swarm Optimization Periodic Point Uniform Design Space Contraction Uniform Design Method 
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 2006

Authors and Affiliations

  • Fei Gao
    • 1
  • Hengqing Tong
    • 1
  1. 1.Department of MathematicsWuhan University of TechnologyWuhanP.R. China

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