Evolution of Search Algorithms Using Graph Structured Program Evolution

  • Shinichi Shirakawa
  • Tomoharu Nagao
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5481)


Numerous evolutionary computation (EC) techniques and related improvements showing effectiveness in various problem domains have been proposed in recent studies. However, it is difficult to design effective search algorithms for given target problems. It is therefore essential to construct effective search algorithms automatically. In this paper, we propose a method for evolving search algorithms using Graph Structured Program Evolution (GRAPE), which has a graph structure and is one of the automatic programming techniques developed recently. We apply the proposed method to construct search algorithms for benchmark function optimization and template matching problems. Numerical experiments show that the constructed search algorithms are effective for utilized search spaces and also for several other search spaces.


Particle Swarm Optimization Search Algorithm Genetic Programming Target Image Template Match 
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 2009

Authors and Affiliations

  • Shinichi Shirakawa
    • 1
  • Tomoharu Nagao
    • 1
  1. 1.Graduate School of Environment and Information SciencesYokohama National UniversityYokohamaJapan

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