Real-Parameter Black-Box Optimization Benchmarking BBOB-2010: Experimental Setup
نویسندگان
چکیده
Quantifying and comparing performance of numerical 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 BBOB 2010 workshop will furnish most of this tedious task for its participants: (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. What remains to be done for participants is to allocate CPU-time, run their favorite black-box real-parameter optimizer in a few dimensions a few hundreds of times and execute the provided post-processing scripts afterwards. Two testbeds are provided, • noise-free functions • noisy functions and participants can freely choose any or all of them. The post-processing provides a quantitative performance assessment in graphs and tables, categorized by function properties like multi-modality, ill-conditioning, global structure, separability,. . . This report describes the experimental setup. The benchmark function definitions, source code of the benchmark functions and for the postprocessing and this report are available at http://coco.gforge.inria. fr/doku.php?id=bbob-2010. ∗NH is with the TAO Team of INRIA Saclay–Île-de-France at the LRI, Université-Paris Sud, 91405 Orsay cedex, France †AA is with the TAO Team of INRIA Saclay–Île-de-France at the LRI, Université-Paris Sud, 91405 Orsay cedex, France ‡SF is with the Research Center PPE, University of Applied Science Vorarlberg, Hochschulstrasse 1, 6850 Dornbirn, Austria §RR is with the TAO Team of INRIA Saclay–Île-de-France at the LRI, Université-Paris Sud, 91405 Orsay cedex, France ¶This report is based to a large extent on the INRIA research report RR-6828
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