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Simulation-Based Optimization with HeuristicLab: Practical Guidelines and Real-World Applications

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Applied Simulation and Optimization

Abstract

Dynamic and stochastic problem environments are often difficult to model using standard problem formulations and algorithms. One way to model and then solve them is simulation-based optimization: Simulations are integrated into the optimization process in order to evaluate the quality of solution candidates and to identify optimized system configurations. Potential solutions are evaluated with a simulation model, which leads to new challenges regarding runtime performance, robustness, and distributed evaluation. In order to design, compare, and parameterize algorithmic approaches it is beneficial to use an optimization framework for algorithm design and evaluation. On the one hand, this chapter shows how arbitrary simulators can be coupled with the open-source HeuristicLab optimization framework. This coupling is implemented in a generic way so that the simulators act as external evaluators. On the other hand, we demonstrate how arbitrary optimizers available within HeuristicLab can be called from a simulator in order to perform complex optimization tasks within the simulation model. In order to illustrate the applicability of these approaches, real-world examples investigated by the authors are discussed. We show here application examples from different fields, namely logistics network design, vendor managed inventory routing, steel slab logistics, production optimization with dispatching rule scheduling, material flow simulation, and layout optimization.

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Notes

  1. 1.

    http://dev.heuristiclab.com.

  2. 2.

    http://heal.heuristiclab.com.

  3. 3.

    https://www.gnu.org/copyleft/gpl.html.

  4. 4.

    http://code.google.com/p/protobuf.

  5. 5.

    http://code.google.com/p/protobuf/wiki/ThirdPartyAddOns.

  6. 6.

    http://www.xjtek.com.

  7. 7.

    http://dev.heuristiclab.com/howtos.

  8. 8.

    http://repast.sourceforge.net.

  9. 9.

    http://github.com/abeham/SimSharp.

  10. 10.

    http://www.bioboost.eu.

  11. 11.

    http://repast.sourceforge.net.

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Acknowledgments

Part of the work described in this chapter were sponsored by the European Regional Development Fund and by Upper Austrian public funds (within the the Regio 13 program - project 4EMobility), by the Austrian Research Promotion Agency (FFG) (within the the Josef Ressel Centre for Heuristic Optimization, the project “NPR” #829679, and the K-project “HOPL” #843532), by the University of Applied Sciences Upper Austria (within the basic research program), and by the seventh framework programme (within the project BioBoost). HeuristicLab is developed by the Heuristic and Evolutionary Algorithm Laboratory and can be downloaded from the official HeuristicLab homepage http://dev.heuristiclab.com.

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Authors and Affiliations

  1. Heuristic and Evolutionary Algorithms Laboratory, School of Informatics, Communications and Media, University of Applied Sciences Upper Austria, Research Center Hagenberg, Softwarepark 11, 4232, Hagenberg, Austria

    Michael Affenzeller, Andreas Beham, Stefan Vonolfen, Erik Pitzer, Stephan M. Winkler, Stephan Hutterer, Michael Kommenda, Monika Kofler, Gabriel Kronberger & Stefan Wagner

  2. Institute for Formal Models and Verification, Johannes Kepler University Linz, Altenberger Straße 69, 4040, Linz, Austria

    Michael Affenzeller, Andreas Beham, Stefan Vonolfen, Stephan Hutterer & Monika Kofler

Authors
  1. Michael Affenzeller
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  2. Andreas Beham
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  3. Stefan Vonolfen
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  4. Erik Pitzer
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  5. Stephan M. Winkler
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  6. Stephan Hutterer
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  7. Michael Kommenda
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  8. Monika Kofler
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  9. Gabriel Kronberger
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  10. Stefan Wagner
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Correspondence to Michael Affenzeller .

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Editors and Affiliations

  1. Aviation Academy, Amsterdam University of Applied Sciences, Amsterdam, Noord-Holland, The Netherlands

    Miguel Mujica Mota

  2. Facultad de Ingeniería, Universidad Nacional Autónoma de México, Mexico City, Mexico

    Idalia Flores De La Mota

  3. Optimisation Research Group, NICTA, Sydney, New South Wales, Australia

    Daniel Guimarans Serrano

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Affenzeller, M. et al. (2015). Simulation-Based Optimization with HeuristicLab: Practical Guidelines and Real-World Applications. In: Mujica Mota, M., De La Mota, I., Guimarans Serrano, D. (eds) Applied Simulation and Optimization. Springer, Cham. https://doi.org/10.1007/978-3-319-15033-8_1

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