Real-Parameter Black-Box Optimization Benchmarking 2010: Experimental Setup

Nikolaus Hansen 1 Anne Auger 1 Steffen Finck 2 Raymond Ros 1
1 TAO - Machine Learning and Optimisation
CNRS - Centre National de la Recherche Scientifique : UMR8623, Inria Saclay - Ile de France, UP11 - Université Paris-Sud - Paris 11, LRI - Laboratoire de Recherche en Informatique
Abstract : Quantifying and comparing performance of optimization algorithms is one important aspect of research in search and optimization. However, this task turns out to be tedious and difficult to realize even in the single-objective case -- at least if one is willing to accomplish it in a scientifically decent and rigorous way. The COCO platform furnishes most of this tedious task for the experimenter: (1) choice and implementation of a well-motivated single-objective benchmark function testbed, (2) design of an experimental set-up, (3) generation of data output for (4) post-processing and presentation of the results in graphs and tables. In this report, the experimental procedure for the BBOB-2010 benchmarking workshop and data formats are thoroughly defined and motivated, and the data presentation is touched on.
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Submitted on : Tuesday, March 9, 2010 - 9:47:54 PM
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Nikolaus Hansen, Anne Auger, Steffen Finck, Raymond Ros. Real-Parameter Black-Box Optimization Benchmarking 2010: Experimental Setup. [Research Report] RR-7215, INRIA. 2010. ⟨inria-00462481⟩

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