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Merge pull request #1864 from numbbo/master
merge back of tagged master into development
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Diff for: README.md

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@@ -141,9 +141,10 @@ Getting Started <a name="Getting-Started"></a>
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Another entry point for your own experiments can be the `code-experiments/examples`
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folder.
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5. Now you can **run** your favorite algorithm on the `bbob` suite (for
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single-objective algorithms) or on the `bbob-biobj` and `bbob-biobj-ext`
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suites (for multi-objective algorithms). Output is automatically generated in the
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5. Now you can **run** your favorite algorithm on the `bbob` and `bbob-largescale` suites
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(for single-objective algorithms), on the `bbob-biobj` suite (for multi-objective
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algorithms), or on the mixed-integer suites (`bbob-mixint` and `bbob-biobj-mixint`
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respectively). Output is automatically generated in the
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specified data `result_folder`. By now, more suites might be available, see below.
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<a name="Getting-Started-pp"></a>
@@ -259,15 +260,19 @@ our issue tracker at https://github.com/numbbo/coco/issues.
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problem inheriting thereby all properties of a coco problem)
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- most other files implement more or less what they say, e.g. the actual
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benchmark functions, transformations, benchmark suites, etc.
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- currently, four benchmark suites and corresponding logging facilities are
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implemented:
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- currently, the following benchmark suites and corresponding logging facilities are
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supported:
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* `bbob`: standard single-objective BBOB benchmark suite with 24 noiseless,
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scalable test functions
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* `bbob-biobj`: a bi-objective benchmark suite, combining 10 selected
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functions from the bbob suite, resulting in 55 noiseless functions
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* `bbob-biobj-ext`: an extended version of the bi-objective `bbob-biobj`
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benchmark suite, adding `bbob` function combinations from the same
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`bbob` function groups, resulting in 92 noiseless functions overall
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* `bbob-largescale`: a version of the `bbob` benchmark suite with dimensions
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20 to 640, employing permuted block-diagonal matrices to reduce the
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execution time for function evaluations in higher dimension.
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* `bbob-mixint`: a mixed-integer version of the original `bbob` and
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`bbob-largescale` suites in which 80% of the variables have been discretized
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* `bbob-biobj-mixint`: a version of the (so far not supported) `bbob-biobj-ext`
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test suite with 92 functions with 80% discretized variables
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* `toy`: a simple, probably easier-to-understand example for reading and testing
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* code-experiments/tools are a few meta-tools, mainly the amalgamate.py to merge all
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at http://numbbo.github.io/coco-doc/bbob-biobj/functions
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- for the **`bbob-largescale`** problem suite
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at http://numbbo.github.io/coco-doc/bbob-largescale/functions
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- for the **`bbob-mixint`** and **`bbob-biobj-mixint`** problem suites, we refer to
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https://hal.inria.fr/hal-02067932/document and to
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http://coco.gforge.inria.fr/preliminary-bbob-mixint-documentation/bbob-mixint-doc.pdf
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* Online documentation of the NumBBO/Coco API (i.e. for the ANSI C code) is available at
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http://numbbo.github.io/coco-doc/C
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* More detailed documentation on how the performance assessement is done can
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- bbob-biobj-ext: http://numbbo.github.io/coco-doc/bbob-biobj/functions/
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- bbob-noisy (only in old code basis): http://coco.lri.fr/downloads/download15.03/bbobdocnoisyfunctions.pdf
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- bbob-largescale: http://numbbo.github.io/coco-doc/bbob-largescale/functions/
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- bbob-mixint and bbob-biobj-mixint: https://hal.inria.fr/hal-02067932/document and
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http://coco.gforge.inria.fr/preliminary-bbob-mixint-documentation/bbob-mixint-doc.pdf
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- bbob-constrained (in progress): http://numbbo.github.io/coco-doc/bbob-constrained/functions/
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