Application, Analysis, and Development of Metaheuristic Algorithms with HeuristicLab, an Open-source Optimization Environment for Research and Education

Author:

  • Stefan Wagner
    Research Center Hagenberg Center of Excellence for Smart Production HEAL, Austria

Abstract:

HeuristicLab [1, 2] is an open-source environment for heuristic optimization that features several metaheuristic optimization algorithms as well as optimization problems. It is developed by the research group Heuristic and Evolutionary Algorithms Laboratory (HEAL) [3] of the University of Applied Sciences Upper Austria and is based on C# and Microsoft .NET. HeuristicLab is used as development platform for several research and industry projects (for example the Josef Ressel Centers SymReg [4] and adaptOp [5]) as well as for teaching metaheuristics in the study programs Software Engineering and Medical- and Bioinformatics in Hagenberg. Over the years HeuristicLab has become more and moreknown within the metaheuristic optimization community and is used by researchers and
lecturers at different universities worldwide. This tutorial demonstrates how to apply, analyze, and develop metaheuristic optimization algorithms using HeuristicLab [1, 2]. It will be shown how to parameterize and execute evolutionary algorithms to solve combinatorial optimization problems (routing, scheduling) as well as data analysis problems (regression, classification). Participants will learn how to assemble different algorithms and parameter settings to a large-scale optimization experiment and how to execute such experiments on multi-core or cluster systems. Furthermore, the experiment results will be compared using HeuristicLab’s interactive charts for visual and
statistical analysis to gain knowledge from the executed test runs. To complete the tutorial, it will be sketched briefly how HeuristicLab can be extended with further optimization problems and how custom optimization algorithms can be developed.

[1] https://dev.heuristiclab.com
[2] https://github.com/heal-research/HeuristicLab
[3] https://heal.heuristiclab.com
[4] https://www.symreg.at
[5] https://www.adaptop.at

Short Bio:

Stefan Wagner received his MSc in computer science in 2004 and his PhD in technical sciences in 2009, both from Johannes Kepler University Linz, Austria. From 2005 to 2009 he worked as associate professor for software project engineering and since 2009 as full professor for complex software systems at the Campus Hagenberg of the University of Applied Sciences Upper Austria. From 2011 to 2018 he was also CEO of the FH OÖ IT GmbH, which is the IT service provider of the University of Applied Sciences Upper Austria. Dr. Wagner is one of the founders of the research group Heuristic and Evolutionary Algorithms Laboratory (HEAL) and is project manager and head architect of the open-source optimization environment HeuristicLab. He works as project manager and key researcher in several R&D projects on production and logistics optimization and his research interests are in the area of combinatorial optimization, evolutionary algorithms, computational intelligence, and parallel and distributed computing.