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International Conference on Agents and Artificial Intelligence

ICAART 2013: Agents and Artificial Intelligence pp 228–244Cite as

Constraint-Handling with Support Vector Decoders

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 449))

Abstract

A comparably new application for support vector machines is their use for meta-modeling the feasible region in constrained optimization problems. Applications have already been developed to optimization problems from the smart grid domain. Still, the problem of a standardized integration of such models into (evolutionary) optimization algorithms was as yet unsolved. We present a new decoder approach that constructs a mapping from the unit hyper cube to the feasible region from the learned support vector model. Thus, constrained problems are transferred into unconstrained ones by space mapping for easier search. We present result from artificial test cases as well as simulation results from smart grid use cases for real power planning scenarios.

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Acknowledgements

The Lower Saxony research network ‘Smart Nord’ acknowledges the support of the Lower Saxony Ministry of Science and Culture through the Niedersächsisches Vorab grant programme (grant ZN 2764).

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Authors and Affiliations

  1. University of Oldenburg, 26129, Oldenburg, Germany

    Jörg Bremer & Michael Sonnenschein

Authors
  1. Jörg Bremer
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  2. Michael Sonnenschein
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Corresponding author

Correspondence to Jörg Bremer .

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Editors and Affiliations

  1. INSTICC, Setúbal, Portugal

    Joaquim Filipe

  2. Instituto de Telecomunicações, Lisbon, Portugal

    Ana Fred

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Bremer, J., Sonnenschein, M. (2014). Constraint-Handling with Support Vector Decoders. In: Filipe, J., Fred, A. (eds) Agents and Artificial Intelligence. ICAART 2013. Communications in Computer and Information Science, vol 449. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-44440-5_14

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  • DOI: https://doi.org/10.1007/978-3-662-44440-5_14

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-44439-9

  • Online ISBN: 978-3-662-44440-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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