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Dafo, a Multi-agent Framework for Decomposable Functions Optimization

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Knowledge-Based Intelligent Information and Engineering Systems (KES 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3684))

Abstract

This paper introduces Dafo, a new multi-agent framework for evolutionary optimization relying on a competitive coevolutionary genetic algorithm, aka LCGA (Loosely Coupled Genetic Algorithm). We describe our solution, discuss of the potential advantages of using an agent based approach and present some results on a real case study: i.e. Inventory Control Parameter (ICP) optimization problem.

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References

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Author information

Authors and Affiliations

  1. Faculty of Sciences, Technology and Communications, 6, rue R. Coudenhove-Kalergi, L-1359, Luxembourg

    Grégoire Danoy & Pascal Bouvry

  2. ENS Mines, 158, cours Fauriel, F-42023, Saint-Etienne

    Olivier Boissier

Authors
  1. Grégoire Danoy
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  2. Pascal Bouvry
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  3. Olivier Boissier
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Editor information

Editors and Affiliations

  1. School of Business, La Trobe University, 3086, Melbourne, Victoria, Australia

    Rajiv Khosla

  2. Centre for SMART systems Engineering Research Centre, University of Brighton, Moulsecoomb, BN2 4GJ, Brighton, UK

    Robert J. Howlett

  3. School of Electrical and Information Engineering, Knowledge Based Intelligent Engineering Systems Centre, University of South Australia, 5095, Mawson Lakes, SA, Australia

    Lakhmi C. Jain

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© 2005 Springer-Verlag Berlin Heidelberg

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Danoy, G., Bouvry, P., Boissier, O. (2005). Dafo, a Multi-agent Framework for Decomposable Functions Optimization. In: Khosla, R., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2005. Lecture Notes in Computer Science(), vol 3684. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11554028_87

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  • DOI: https://doi.org/10.1007/11554028_87

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28897-8

  • Online ISBN: 978-3-540-31997-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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