modified: 10. Sep. 2005

Documentation

API Documentation

The HeuristicLab API Documentation has been generated with the NDoc Code Documentation Generator for .NET. It is included in the HeuristicLab Environment itself and can also be downloaded from this page. Additionally an online version of the documentation is provided below.

 

Source Examples

The source code of several plug-ins can be downloaded from the plug-in download page. Especially the SGA and TSP plug-ins can be used as reference implementations. So feel free to use them as templates for any other algortihm or problem plug-ins.

 

Papers & Reports

  • S. Wagner, M. Affenzeller
    "The HeuristicLab Optimization Environment". Technical Report. Institute of Formal Models and Verification, Johannes Kepler University Linz, Austria. 2004. (pdf, ps, ps.gz)
  • S. Wagner, M. Affenzeller
    "HeuristicLab Grid - A Flexible and Extensible Environment for Parallel Heuristic Optimization". Proceedings of the 15th International Conference on Systems Science, vol. 1, pp. 289-296. Oficyna Wydawnicza Politechniki Wroclawskiej, 2004. (pdf)

 

Tutorials

Due to a severe lack of human resources we are not able to provide any tutorials yet. If you are interested in writing a tutorial about HeuristicLab itself, HeuristicLab plug-in development, or any specific algorithm or problem, please write an e-mail to support@heuristiclab.com.

 

Plug-In Documentation

For some HeuristicLab plug-ins additional documentation is available:

  • ES
    Evolution Strategy implemented by Mihaela Ionescu
    Project Paper (pdf in German)
  • GBML
    Genetic Algorithm-Based Machine Learning implemented by Dietmar Langer
    Plug-In Documentation (chm in German)
  • GP
    Generic Genetic Programming Problem implemented by Jörg Pührer
    Plug-In Documentation (chm in German)
  • GR
    Genetic (Symbolic) Regression Problem implemented by Reinhard Zierhofer
    Master Thesis (pdf in German)
  • SAT
    Satisfiability Problem implemented by Florian Lonsing
    Project Paper (pdf)
  • SEGA
    Segregative Genetic Algorithm implemented by Michael Affenzeller and Stefan Wagner
    Journal Article (pdf)
  • SGAML
    Standard Genetic Algorithm for Machine Learning implemented by Dietmar Langer
    Plug-In Documentation (chm in German)
  • SS
    Scatter Search implemented by Andreas Beham
    Plug-In Documentation (chm)
  • STS
    Standard Tabu Search implemented by Andreas Beham
    Plug-In Documentation (chm)
  • Sudoku
    Description of Sudoku at derStandard.at (in German)
  • VRP
    Vehicle Routing Problem implemented by Michael Bögl
    Project Paper (pdf in German)