| layout | permalink | nav_order | title | dataDir |
|---|---|---|---|---|
default |
/bbob-constrained/ |
7 |
bbob-constrained |
<script type="text/javascript" src="{{site.baseurl}}/sort-table.js"></script>
In the table below, you will find all official algorithm data sets on the bbob-constrained test suite, together with their year of publication, the authors, and related PDFs for each data set. Links to the source code to run the corresponding experiments/algorithms are provided whenever available.
To sort the table, simply click on the table header of the corresponding column.
{:.js-sort-table}
| Number | Algorithm Name | Year | Author(s) | link to data | related PDFs, source code, and remarks |
|---|---|---|---|---|---|
| constrained-000 | RandomSearch-5 | 2022 | Dufossé | [data]({{ page.dataDir }}/2022/RandomSearch-5_Dufosse.tgz) | source code |
| constrained-001 | AL1-CMA-ES | 2022 | Dufossé and Atamna | [data]({{ page.dataDir }}/2022/AL1-CMA-ES_Dufosse.tgz) | CMA-ES with Augmented Lagrangian fitness, pycma version, parameter setting 1 as compared by Dufosse and Atamna for BBOB-2022 |
| constrained-002 | AL2-CMA-ES | 2022 | Dufossé and Atamna | [data]({{ page.dataDir }}/2022/AL2-CMA-ES_Dufosse.tgz) | CMA-ES with Augmented Lagrangian fitness, pycma version, parameter setting 2 as compared by Dufosse and Atamna for BBOB-2022 |
| constrained-003 | AL3-CMA-ES | 2022 | Dufossé and Atamna | [data]({{ page.dataDir }}/2022/AL3-CMA-ES_Dufosse.tgz) | CMA-ES with Augmented Lagrangian fitness, pycma version, parameter setting 3 (default) as compared by Dufosse and Atamna for BBOB-2022 |
| constrained-004 | AL4-CMA-ES | 2022 | Dufossé and Atamna | [data]({{ page.dataDir }}/2022/AL4-CMA-ES_Dufosse.tgz) | CMA-ES with Augmented Lagrangian fitness, pycma version, parameter setting 4 as compared by Dufosse and Atamna for BBOB-2022 |
| constrained-005 | BPepsMAg | 2022 | Hellwig and Beyer | [data]({{ page.dataDir }}/2022/BPepsMAg_Hellwig.tgz) | Matrix Adaptation Evolution Strategy with restarts and BIPOP strategy, using up to three different constraint handling techniques, as compared by Hellwig and Beyer for BBOB-2022 |
| constrained-006 | COBYLA | 2022 | Dufossé and Atamna | [data]({{ page.dataDir }}/2022/COBYLA_Dufosse.tgz) | Constrained Optimization BY Linear Approximation (implemented in SciPy as a wrapper around Powell's fortran code) compared by Dufosse and Atamna for BBOB-2022 |
| constrained-007 | epsMAg | 2022 | Hellwig and Beyer | [data]({{ page.dataDir }}/2022/epsMAg_Hellwig.tgz) | Matrix Adaptation Evolution Strategy, using up to three different constraint handling techniques, as compared by Hellwig and Beyer for BBOB-2022 |
| constrained-008 | fmincon | 2022 | Hellwig and Beyer | [data]({{ page.dataDir }}/2022/fmincon_Hellwig.tgz) | default fmincon from Matlab2021b, as compared by Hellwig and Beyer for BBOB-2022 |