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HeuristicLab is a framework for heuristic and evolutionary algorithms that is developed by members of the Heuristic and Evolutionary Algorithms Laboratory (HEAL) since 2002. The developers team of HeuristicLab uses this page to coordinate efforts to improve and extend HeuristicLab.
  • Graphical User Interface
  • Algorithm Prototyping
  • Evolutionary Algorithms
  • Genetic Programming
  • Data Analysis
  • Simulation-based Optimization
  • Experiment Design and Analysis
  • Plugin-based Architecture
At a glance:
Getting Started: Find out more about HeuristicLab on the About and the Features page, read the User Manual or follow our Blog. For developers who wish to contribute to HeuristicLab we provide development guidelines, demos and how tos. If you find any bugs or have additional questions or feedback, please have a look at our Feedback & Support page and don't hesitate to contact us.
Developers: Check out the Roadmap and monitor the development progress and changes. Read the documentation to see how you can extend HeuristicLab with your own plugins. Find out more about the research group HEAL, the individual contributors and software projects and scientific publications that have been realized with HeuristicLab on HEAL is a research group of the University of Applied Sciences Upper Austria.
Publications and Projects: The HeuristicLab software framework has been successfully used in many applied research projects and scientific papers, book chapters and journal articles. A full overview can be found on the research group homepage, but an overview of the most important Publications and selected projects can be found here.
Citation: If you publish any results derived with HeuristicLab, we would be grateful if you cite the following reference in your publications:

Wagner, S. et al. Architecture and Design of the HeuristicLab Optimization Environment. In Advanced Methods and Applications in Computational Intelligence, Topics in Intelligent Engineering and Informatics Series, pp. 197-261. Springer (2014) PDF BibTeX

The original publication is available at SpringerLink.

Imprint: Statement of the ownership/authorship of this webpage plus contact information can be found here.