Mixed-effects modeling of optimisation algorithm performance

Gagliolo, M.;Legrand, Catherine;Birattari, M.
(2009) Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics. Second International Workshop, SLS 2009 — Location: Brussels, Belgium (3.September.2008)

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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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Gagliolo, M., Legrand, C., & Birattari, M. (2009). Mixed-effects modeling of optimisation algorithm performance. In Stutzle, T.; Birattari, M.; Hoos, H.H.; (ed.), Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics. Second International Workshop, SLS 2009 (p. p. 150-154). Springer verlag. https://hdl.handle.net/2078.5/223286