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Copy file name to clipboardExpand all lines: README.md
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-`Java`
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-`MATLAB/Octave`
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-`Python`
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-`Rust`
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Code for others might be available in branched code.
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Contributions to link further languages (including a better
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For more general information:
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- read our benchmarking guidelines introduction [COCO: A Platform for Comparing Continuous Optimizers in a Black-Box Setting (pdf)]((https://www.tandfonline.com/eprint/DQPF7YXFJVMTQBH8NKR8/pdf?target=10.1080/10556788.2020.1808977)) or at [arXiv](https://arxiv.org/abs/1603.08785).
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- read our benchmarking guidelines introduction [COCO: A Platform for Comparing Continuous Optimizers in a Black-Box Setting (pdf)](https://www.tandfonline.com/eprint/DQPF7YXFJVMTQBH8NKR8/pdf?target=10.1080/10556788.2020.1808977) or at [arXiv](https://arxiv.org/abs/1603.08785).
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- read the [COCO experimental setup](http://numbbo.github.io/coco-doc/experimental-setup) description
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- see the [`bbob-biobj` and `bbob-biobj-ext` COCO multi-objective functions testbed](http://numbbo.github.io/coco-doc/bbob-biobj/functions) documentation and the [specificities of the performance assessment for the bi-objective testbeds](http://numbbo.github.io/coco-doc/bbob-biobj/perf-assessment).
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- consult the [BBOB workshops series](http://numbbo.github.io/workshops),
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***C**: `make`, such as GNU make (when using [GNU make for Windows](http://gnuwin32.sourceforge.net/packages/make.htm), make sure that your ``CC`` environment variable is set to `gcc` by potentially typing `set CC=gcc` if you see an error).
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***Java**: `gcc` and any Java Development Kit (JDK), such that `javac` and `javah` are accessible
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(i.e. in the system path).
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(i.e. in the system path).
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***Rust**: For details, take a look at the [Rust Readme](./code-experiments/build/rust/README.md)
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***MATLAB**: at least MATLAB 2008, for details, see [here](./code-experiments/build/matlab/README.md)
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***Python on Windows with MinGW**: Python 2.7 and the Microsoft compiler package for Python 2.7
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containing VC9, available [here](https://www.microsoft.com/en-us/download/details.aspx?id=44266).
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}
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```
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Links and Documentation <a name="Links"></a>
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-----------------------
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Links About the Workshops and Data <a name="Links"></a>
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----------------------------------
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* The [_BBOB workshop series_](http://numbbo.github.io/workshops), which uses the
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found at https://numbbo.github.io/ppdata-archive
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* Stay informed about the BBOB workshop series and releases of the NumBBO/Coco software
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by registering via [this form](https://docs.google.com/forms/d/1GS48SXGjapUu6WY6Zt-Ma5HCl2izq4ydT7sMa5ujUDI)
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* Read about the basic principles behind the Coco platform in [COCO: A Platform for Comparing Continuous Optimizers in a Black-Box Setting (pdf)](https://www.tandfonline.com/eprint/DQPF7YXFJVMTQBH8NKR8/pdf?target=10.1080/10556788.2020.1808977) or at [arXiv](https://arxiv.org/abs/1603.08785).
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* For details on the experimental set-up to carry out the benchmarking
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please refer to http://numbbo.github.io/coco-doc/experimental-setup/.
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* More detailed documentation of the existing benchmark suites can be found here:
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- for the **`bbob`** problem suite at https://numbbo.github.io/gforge/downloads/download16.00/bbobdocfunctions.pdf
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with the experimental setup at http://coco.lri.fr/downloads/download15.03/bbobdocexperiment.pdf
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- for the **`bbob-biobj`** and **`bbob-biobj-ext`** problem suites
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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 https://arxiv.org/pdf/1903.06396.pdf
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- for the **`bbob-mixint`** and **`bbob-biobj-mixint`** problem suites, we refer to
* 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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be found at http://numbbo.github.io/coco-doc/perf-assessment/.
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* Downloading this repository
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- via the above green "Clone or Download" button or
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- by typing `git clone https://github.com/numbbo/coco.git` or
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* General introduction: [COCO: A Platform for Comparing Continuous Optimizers in a Black-Box Setting (pdf)](https://www.tandfonline.com/eprint/DQPF7YXFJVMTQBH8NKR8/pdf?target=10.1080/10556788.2020.1808977) or at [arXiv](https://arxiv.org/abs/1603.08785)
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