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International Workshop on Engineering Stochastic Local Search Algorithms

SLS 2009: Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics pp 150–154Cite as

Mixed-Effects Modeling of Optimisation Algorithm Performance

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5752))

Abstract

The learning curves of optimisation algorithms, plotting the evolution of the objective vs. runtime spent. can be viewed as a sample of longitudinal data. In this paper we describe mixed-effects modeling, a standard technique in longitudinal data analysis, and give an example of its application to algorithm performance modeling.

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Author information

Authors and Affiliations

  1. IRIDIA, CoDE, Université Libre de Bruxelles, Brussels, Belgium

    Matteo Gagliolo & Mauro Birattari

  2. Faculty of Informatics, University of Lugano, Lugano, Switzerland

    Matteo Gagliolo

  3. Institut de Statistique, Université Catholique de Louvain, Louvain-la-Neuve, Belgium

    Catherine Legrand

Authors
  1. Matteo Gagliolo
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  2. Catherine Legrand
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  3. Mauro Birattari
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Editor information

Editors and Affiliations

  1. IRIDIA, CoDE, Université Libre de Bruxelles, Avenue F. Roosevelt 50, CP 194/6, 1050, Brussels, Belgium

    Thomas Stützle

  2. IRIDIA, CoDE, Université Libre de Bruxelles, Av. F. Roosevelt 50, CP 194/6, 1050, Brussels, Belgium

    Mauro Birattari

  3. Computer Science Department, University of British Columbia, 2366 Main Mall, V6T 1Z4, Vancouver, BC, Canada

    Holger H. Hoos

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© 2009 Springer-Verlag Berlin Heidelberg

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Gagliolo, M., Legrand, C., Birattari, M. (2009). Mixed-Effects Modeling of Optimisation Algorithm Performance. In: Stützle, T., Birattari, M., Hoos, H.H. (eds) Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics. SLS 2009. Lecture Notes in Computer Science, vol 5752. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03751-1_17

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  • DOI: https://doi.org/10.1007/978-3-642-03751-1_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-03750-4

  • Online ISBN: 978-3-642-03751-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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