Results from BBOB-2009: all functions COCO (COmparing Continuous Optimisers) is a platform for systematic and sound comparisons of real-parameter global optimisers. COCO provides benchmark function testbeds, experimentation templates which are easy to parallelize, and tools for processing and visualizing data generated by one or several optimizers. The COCO platform has been used for the Black-Box-Optimization-Benchmarking (BBOB) workshops that took place during the GECCO conference in 2009, 2010, 2012, 2013, and in 2015-2017. It was also used at the IEEE Congress on Evolutionary Computation (CEC'2015) in Sendai, Japan. The COCO source code is available at the downloads page.

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Internal wiki:

Selected Results

The figures show selected results from BBOB 2009. The empirical runtime distribution is shown for six subgroups of the BBOB functions. Click on the respective figures for more details. (At the top of this page the aggregated results over all functions are shown).

 Results from BBOB-2009: separable functions   Results from BBOB-2009: moderate functions  Results from BBOB-2009: ill-conditioned functions  Results from BBOB-2009: multimodal structured functions  Results from BBOB-2009: multimodal weakly structured functions  Results from BBOB-2009: non-smooth functions

Current BBOB Functions

The current 24 noiseless test functions are

Only f1 and f5 are purely quadratic or linear respectively.

See also N. Hansen et al (2010): Comparing Results of 31 Algorithms from the Black-Box Optimization Benchmarking BBOB-2009. Workshop Proceedings of the GECCO Genetic and Evolutionary Computation Conference 2010, ACM. 1)

The current 30 noisy test functions are


1) This work was partially funded by FUI of System@tic Paris-Region ICT cluster through contract DGT 117 407 Complex Systems Design Lab (CSDL), and by the ANR-2010-COSI-002 grant (SIMINOLE) of the French National Research Agency.
2) Work on Coco is also funded via the ANR project NumBBO.
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