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Distributed Genetic Algorithms with an Application to Portfolio Selection Problems

  • A. Loraschi
  • Marco Tomassini
  • A. Tettamanzi
  • Paolo Verda

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.

Keywords

Genetic Algorithm Portfolio Selection Efficient Frontier Portfolio Selection Problem Island Model 
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/Wien 1995

Authors and Affiliations

  • A. Loraschi
    • 1
  • Marco Tomassini
    • 2
    • 3
  • A. Tettamanzi
    • 4
  • Paolo Verda
    • 5
  1. 1.SIGE Consulenza S.P.A.MilanoItaly
  2. 2.Centro Svizzero di Calcolo ScientificoMannoSwitzerland
  3. 3.Laboratoire de Systèmes Logiques Ecole PolytechniqueFédérale de LausanneSwitzerland
  4. 4.Dip.to di Scienze dell’InformazioneUniversita’ degli Studi di MilanoMilanoItaly
  5. 5.Institut d’InformatiqueUniversité de FribourgFribourgSwitzerland

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