Ārtap is a framework for robust design optimization in Python. It contains an integrated, multi-physical FEM solver: Agros suite, furthermore it provides simple interfaces for commercial FEM solvers (COMSOL) and meta-heuristic, Bayesian or neural network-based optimization algorithms surrogate modeling techniques and neural networks.


Ārtap core and its dependencies are available as wheel packages for Windows and Linux* distributions:
We recommend installing Ārtap in a virtual environment.

pip install --upgrade pip  # make sure that pip is reasonably new
pip install artap


You can install the full package, which contains the agrossuite python package, as well,  by the following command:

pip install artap[full]

The latest version of Agros-suite can be achieved as a pip package independently*:

pip install agrossuite

*The agrossuite package currently supports only linux based systems.

You can find some Tutorials and open Ārtap projects here: https://github.com/artap-team/Artap-OpenProjects

Source Code

Source code is located in the Git repository. You can clone this repository.

git clone https://github.com/artap-framework/artap.git


If you use Ārtap in your research, the developers would be grateful if you would cite the relevant publications:

[1] Karban, Pavel, David Pánek, Tamás Orosz, Iveta Petrášová, and Ivo Doležel. “FEM based robust design optimization with Agros and Ārtap.” Computers & Mathematics with Applications (2020) https://doi.org/10.1016/j.camwa.2020.02.010.

[2] Pánek, David, Tamás Orosz, and Pavel Karban. ” Ārtap: robust design optimization framework for engineering applications.” arXiv preprint arXiv:1912.11550 (2019).


[3] Karban, P., Pánek, D., & Doležel, I. (2018). Model of induction brazing of nonmagnetic metals using model order reduction approach. COMPEL-The international journal for computation and mathematics in electrical and electronic engineering, 37(4), 1515-1524, https://doi.org/10.1108/COMPEL-08-2017-0356.

[4] Pánek, D., Orosz, T., Kropík, P., Karban, P., & Doležel, I. (2019, June). Reduced-Order Model Based Temperature Control of Induction Brazing Process. In 2019 Electric Power Quality and Supply Reliability Conference (PQ) & 2019 Symposium on Electrical Engineering and Mechatronics (SEEM) (pp. 1-4). IEEE, 10.1109/PQ.2019.8818256.

[5] Pánek, D., Karban, P., & Doležel, I. (2019). Calibration of Numerical Model of Magnetic Induction Brazing. IEEE Transactions on Magnetics, 55(6), 1-4, 10.1109/TMAG.2019.2897571.

[6] Pánek, D., Orosz, T., Karban, P., & Doležel, I. (2020), “Comparison of simplified techniques for solving selected coupled electroheat problems”, COMPEL – The international journal for computation and mathematics in electrical and electronic engineering, Vol. 39 No. 1, pp. 220-230. https://doi.org/10.1108/COMPEL-06-2019-0244

[7] Orosz, T.; Pánek, D.; Karban, P. FEM Based Preliminary Design Optimization in Case of Large Power Transformers. Appl. Sci. 2020, 10, 1361, https://doi.org/10.3390/app10041361.


If you have any questions, do not hesitate to contact us: artap.framework@gmail.com


Ārtap is published under MIT license.