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A Hybrid Genetic Algorithm for the Hexagonal Tortoise Problem

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Genetic and Evolutionary Computation — GECCO 2003 (GECCO 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2723))

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Abstract

We propose a hybrid genetic algorithm for the hexagonal tortoise problem. We combined the genetic algorithm with an efficient local heuristic and aging mechanism. Another search heuristic which focuses on the space around existing solutions is also incorporated into the genetic algorithm. With the proposed algorithm, we could find the optimal solutions of up to a fairly large problem.

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Author information

Authors and Affiliations

  1. School of Computer Science and Engineering, Seoul National University, Seoul, 141-742, Korea

    Heemahn Choe, Sung-Soon Choi & Byung-Ro Moon

Authors
  1. Heemahn Choe
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  2. Sung-Soon Choi
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  3. Byung-Ro Moon
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Editor information

Editors and Affiliations

  1. Lawrence Livermore National Laboratory, Center for Applied Scientific Computing (CASC), 7000 East Avenue, L-561, Livermore, CA, 94550, USA

    Erick Cantú-Paz

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Choe, H., Choi, SS., Moon, BR. (2003). A Hybrid Genetic Algorithm for the Hexagonal Tortoise Problem. In: Cantú-Paz, E., et al. Genetic and Evolutionary Computation — GECCO 2003. GECCO 2003. Lecture Notes in Computer Science, vol 2723. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45105-6_98

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  • DOI: https://doi.org/10.1007/3-540-45105-6_98

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40602-0

  • Online ISBN: 978-3-540-45105-1

  • eBook Packages: Springer Book Archive

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