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OpenMDAO
What it is
OpenMDAO is a free, open-source Python framework for systems analysis and multidisciplinary optimization, available for Linux and self-hosted use. It focuses on gradient-based optimization with analytic derivatives, including design problems with hundreds or thousands of variables. Models are assembled from components and groups, while drivers run optimization algorithms or design-of-experiments workflows. Nonlinear and linear solvers can be placed at different levels of a model hierarchy. Derivative tools include analytic partials, finite-difference and complex-step approximations, derivative checking, and forward or reverse total derivative calculations. MPI features support parallel subsystems and distributed variables across processes; parallel computing can also support gradient-free optimization, mixed-integer nonlinear programming, and design-space exploration. Users can visualize models and optimization progress, and record or read model and solver cases. Related libraries include Dymos for transient modeling and optimal control, and pyCycle for turbine engine cycle analysis. OpenMDAO is licensed under Apache 2.0. Its supported 3.x line requires Python 3.10 or later, and its API may change during active development.
For and against
For
- Free under the Apache 2.0 license.
- Supports analytic derivatives and derivative checking.
- MPI supports parallel subsystems and distributed variables.
- Includes model visualizations and optimization progress plots.
- Related libraries support optimal control and engine cycle analysis.
Against
- The supported 3.x line requires Python 3.10 or later.
- The API may change during active development.
- Some parallel derivative methods require MPI.
The verdict
OpenMDAO offers a broad set of modeling, solver, derivative, and parallel-computing capabilities for multidisciplinary optimization. Its Python requirement and active-development API changes are worth considering before adopting it.
Who it suits
OpenMDAO may suit engineers and researchers building complex system models or optimization workflows. Listed application areas include cubesat design and mission planning, wind turbine design, and unconventional aircraft concepts.
Plans and prices
OpenMDAO
open-source framework · Apache 2.0 license
Read 4 Oct 2026 · openmdao.org
On the record
- Derivative tools
- It supports analytic partial derivatives, finite-difference and complex-step approximations, derivative checking, and forward or reverse total derivative calculations.openmdao.org · read 4 Oct 2026
- Installation
- The project documents installation from PyPI or a cloned GitHub repository, with optional dependency sets for testing, documentation, and visualization.github.com · read 4 Oct 2026
- Intended users
- The project describes applications including cubesat design and mission planning, wind turbine design, and unconventional aircraft concepts.openmdao.org · read 4 Oct 2026
- License
- OpenMDAO is released under the Apache 2.0 license, which the project says permits proprietary software to be integrated without making it open source.openmdao.org · read 4 Oct 2026
- Model structure
- Models are built from components and groups, with drivers that can run optimization algorithms or design of experiments.openmdao.org · read 4 Oct 2026
- Other optimization
- Its parallel computing features can also support gradient-free optimization, mixed-integer nonlinear programming, and design space exploration.openmdao.org · read 4 Oct 2026
- Parallel computing
- MPI features can run parallel subsystems and distributed variables across multiple processes.openmdao.org · read 4 Oct 2026
- Parallel dependency limit
- The documentation says parallel finite-difference and complex-step derivative approximation requires MPI and may not run on Colab or Binder.openmdao.org · read 4 Oct 2026
- Primary method
- The project focuses on gradient-based optimization with analytic derivatives for design spaces with hundreds or thousands of design variables.openmdao.org · read 4 Oct 2026
- Purpose
- OpenMDAO is an open-source Python framework for systems analysis and multidisciplinary optimization.openmdao.org · read 4 Oct 2026
- Related libraries
- The project identifies Dymos for transient modeling and optimal control and pyCycle for turbine engine cycle analysis as libraries built on OpenMDAO.openmdao.org · read 4 Oct 2026
- Solver features
- OpenMDAO provides nonlinear and linear solvers that can be placed at different levels of a model hierarchy.openmdao.org · read 4 Oct 2026
- Version requirements
- The repository says the current supported OpenMDAO 3.x line requires Python 3.10 or later and that its API may change periodically while in active development.github.com · read 4 Oct 2026
- Visualization and recording
- Documented features include model visualizations, optimization progress plots, and recording and reading model or solver cases.openmdao.org · read 4 Oct 2026
