Offspring Generation Method Using Delaunay Triangulation for Real-Coded Genetic Algorithms

  • Hisashi Shimosaka
  • Tomoyuki Hiroyasu
  • Mitsunori Miki
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4193)


To design crossover operators with high search ability in real-coded Genetic Algorithms, it will be efficient to utilize both information regarding the parent distribution and the landscape of the objective function. Here, we propose a new offspring generation method using Delaunay triangulation. The proposed method can concentrate offspring in regions with a satisfactory evaluation value, inheriting the parent distribution. Through numerical examples, the proposed method was shown to be capable of deriving the optimum with a smaller population size and lower number of evaluations than Simplex Crossover, which uses only information of the parent distribution.


Voronoi Diagram Crossover Operator Expansion Rate Delaunay Triangulation Parent Distribution 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Hisashi Shimosaka
    • 1
  • Tomoyuki Hiroyasu
    • 2
  • Mitsunori Miki
    • 2
  1. 1.Graduate School of EngineeringDoshisha UniversityKyotoJapan
  2. 2.Department of EngineeringDoshisha University 

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