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Artificial Neural Nets and Genetic Algorithms pp 384–387Cite as

Distributed Genetic Algorithms with an Application to Portfolio Selection Problems

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Abstract

This paper presents a PVM-based coarse-grained distributed genetic algorithm implemented on workstation clusters. After successfully evaluating the algorithm with standard test functions, we apply it to a hard real-world portfolio selection problem. The distributed version easily outperforms sequential genetic algorithms and shows promise for difficult management applications.

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References

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Author information

Authors and Affiliations

  1. SIGE Consulenza S.P.A., Milano, Italy

    A. Loraschi

  2. Centro Svizzero di Calcolo Scientifico, Manno, Switzerland

    Marco Tomassini

  3. Laboratoire de Systèmes Logiques Ecole Polytechnique, Fédérale de Lausanne, Switzerland

    Marco Tomassini

  4. Dip.to di Scienze dell’Informazione, Universita’ degli Studi di Milano, Milano, Italy

    A. Tettamanzi

  5. Institut d’Informatique, Université de Fribourg, Fribourg, Switzerland

    Paolo Verda

Authors
  1. A. Loraschi
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  2. Marco Tomassini
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  3. A. Tettamanzi
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  4. Paolo Verda
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© 1995 Springer-Verlag/Wien

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Loraschi, A., Tomassini, M., Tettamanzi, A., Verda, P. (1995). Distributed Genetic Algorithms with an Application to Portfolio Selection Problems. In: Artificial Neural Nets and Genetic Algorithms. Springer, Vienna. https://doi.org/10.1007/978-3-7091-7535-4_100

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  • DOI: https://doi.org/10.1007/978-3-7091-7535-4_100

  • Publisher Name: Springer, Vienna

  • Print ISBN: 978-3-211-82692-8

  • Online ISBN: 978-3-7091-7535-4

  • eBook Packages: Springer Book Archive

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