gemseo-umdo is a plugin of the library GEMSEO,
dedicated to multidisciplinary optimization (MDO) under uncertainty.
The main goal of gemseo-umdo is to extend GEMSEO
to MDO under uncertainty.
Given a collection of disciplines, we are interested in solving a problem like
$$ \begin{align} &\underset{x\in\mathcal{X}}{\operatorname{minimize}}& & \mathbb{E}[f(x,U)]+\kappa\times\mathbb{S}[f(x,U)] \ &\operatorname{subject;to} & &\mathbb{P}[g(x,U)\geq 0] \leq \varepsilon \end{align} $$
by selecting an MDO formulation to handle the multidisciplinary coupling and an estimation technique to approximate the statistics.
gemseo-umdo also proposes advanced techniques
for uncertainty quantification and management (UQ&M).
In presence of multilevel simulators,
multilevel Monte Carlo (MLMC) sampling can reduce
the variance of the statistics estimators.
Another variance reduction technique
consists of using the outputs of surrogate models
as control variates,
even moderately correlated with the original models.
A third facet of gemseo-umdo is the visualization toolbox
to display the propagation of the uncertainties
through a multidisciplinary system
as well as the interaction between the uncertain input variables.
Install the latest version with pip install gemseo-umdo.
See pip for more information.
Please use the gitlab issue tracker to submit bugs or questions.
See the contributing section of GEMSEO.
FAQs
Robust MDO and advanced UQ with GEMSEO.
We found that gemseo-umdo demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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