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Genetic Programming and Evolvable Machines

, Volume 15, Issue 2, pp 215–218 | Cite as

Software review: the HeuristicLab framework

  • Achiya Elyasaf
  • Moshe Sipper
SOFTWARE REVIEW

Introduction

HeuristicLab homepage: http://dev.heuristiclab.com

Computer scientists often find themselves debating whether they should use (and extend) an existing system or develop their own. The onerous task of learning how to operate an existing system can be a severe overhead when all one wishes is to conduct a small experiment. However, especially where extended experiments are to be conducted, in the long run, a system that is extensible, flexible, modular, and usable, can save valuable time.

HeuristicLab [6, 7] is a graphical user interface (GUI) based framework for heuristic and evolutionary algorithms, designed for ease of use.

It offers a plugin-based architecture (which enables users to add custom extensions without knowing the whole of the source code), a domain-independent model to represent arbitrary search algorithms, support for graphical user interfaces, and the ability to accommodate parallel algorithms.

HeuristicLab has been under development since 2002 by members of...

Keywords

Evolutionary Algorithm Graphical User Interface Graphic Processing Unit Fitness Evaluation Function Video Tutorial 
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.

References

  1. 1.
    ECLab Evolutionary Computation Laboratory, George Mason University: ECJ 2.0 (2010). http://cs.gmu.edu/eclab/projects/ecj/
  2. 2.
    HEAL: Heuristic and Evolutionary Algorithms Laboratory. http://heal.heuristiclab.com/
  3. 3.
    HEAL (Heuristic and Evolutionary Algorithms Laboratory): Official HeuristicLab discussion group. http://groups.google.com/forum/?fromgroups=#!forum/heuristiclab/
  4. 4.
    J.A. Parejo, A. Ruiz-Cortés, S. Lozano, P. Fernández, Metaheuristic optimization frameworks: a survey and benchmarking. Soft Comput. 16(3), 527–561 (2011). doi: 10.1007/s00500-011-0754-8 CrossRefGoogle Scholar
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    The Mono project website. http://www.mono-project.com
  6. 6.
    S. Wagner, Heuristic optimization software systems - modeling of heuristic optimization algorithms in the HeuristicLab software environment. Ph.D. thesis, Johannes Kepler University, Linz, Austria (2009)Google Scholar
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    S. Wagner, G. Kronberger, A. Beham, M. Kommenda, A. Scheibenpflug, E. Pitzer, S. Vonolfen, M. Kofler, S. Winkler, V. Dorfer, M. Affenzeller, in Architecture and design of the HeuristicLab optimization environment, ed. by R. Klempous, J. Nikodem, W. Jacak, Z. Chaczko. Advanced Methods and Applications in Computational Intelligence, Topics in Intelligent Engineering and Informatics, vol 6. (Springer, New York, 2014), pp. 197–261. doi: 10.1007/978-3-319-01436-4_10.
  8. 8.
    D.R. White, Software review: the ECJ toolkit. Genet. Program. Evolvable Mach. 13(1), 65–67 (2012). doi: 10.1007/s10710-011-9148-z CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.Ben-Gurion University of the NegevBe’er ShevaIsrael

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