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The EvA2 Optimization Framework

  • Marcel Kronfeld
  • Hannes Planatscher
  • Andreas Zell
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6073)

Abstract

We present EvA2, a comprehensive metaheuristic optimization framework with emphasis on Evolutionary Algorithms. It presents a modular structure of interfaces and abstract classes for the implementation of both optimization problems and solvers. End users may choose among several layers of abstraction for an entrance point meeting their requirements on ease of use and access to extensive functionality. The EvA2 framework has been applied successfully in several academic as well as industrial cooperations and is extended continuously. It is freely available under an open source license (LGPL).

Keywords

Extensive Functionality Open Source License Heuristic Operator Industrial Cooperation Multiobjective Optimization Method 
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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References

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    de Paly, M., Zell, A.: Optimal Irrigation Scheduling with Evolutionary Algorithms. In: Proceedings of Applications of Evolutionary Computing: EvoWorkshops 2009, vol. 5484, pp. 142–151 (2009)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Marcel Kronfeld
    • 1
  • Hannes Planatscher
    • 1
  • Andreas Zell
    • 1
  1. 1.Wilhelm-Schickard-Institute for Computer ScienceUniversity of TübingenGermany

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