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Genetic Algorithm to Optimize Fitness Function with Sampling Error and its Application to Financial Optimization Problem

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Evolutionary Computation in Dynamic and Uncertain Environments

Part of the book series: Studies in Computational Intelligence ((SCI,volume 51))

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Author information

Authors and Affiliations

  1. Research and Development Section, Hitachi East Japan Solutions Ltd, 2-16-10, Honcho, Aoba, 980-0014, Senadi, Japan

    Masaru Tezuka

  2. Information Initiative Center, Hokkaido University, Kita 11 Nishi 5, 060-0811, Sapporo, Japan

    Masaharu Munetomo

  3. Information Initiative Center, Hokkaido University, Kita 11 Nishi 5, 060-0811, Sapporo, Japan

    Kiyoshi Akama

Authors
  1. Masaru Tezuka
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  2. Masaharu Munetomo
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  3. Kiyoshi Akama
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Leicester, University Road, LE1 7RH, Leiceste, UK

    Shengxiang Yang

  2. School of Computer Engineering, Nanyang Technological University, Blk N4, 2b-39, Nanyang Avenue, 639798, Singapore

    Yew-Soon Ong

  3. Honda Research Institute Europe, Carl-Legien-Str 30, 63073, Offenbach am Main, Germany

    Yaochu Jin

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© 2007 Springer-Verlag Berlin Heidelberg

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Tezuka, M., Munetomo, M., Akama, K. (2007). Genetic Algorithm to Optimize Fitness Function with Sampling Error and its Application to Financial Optimization Problem. In: Yang, S., Ong, YS., Jin, Y. (eds) Evolutionary Computation in Dynamic and Uncertain Environments. Studies in Computational Intelligence, vol 51. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-49774-5_18

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  • DOI: https://doi.org/10.1007/978-3-540-49774-5_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-49772-1

  • Online ISBN: 978-3-540-49774-5

  • eBook Packages: EngineeringEngineering (R0)

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