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OpenMDAO

openmdao.org

Free plan LinuxSelf-hosted
Visit openmdao.org
Spec score 7.6 #10 of 20 in Generative Design Software

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 spaces with hundreds or thousands of variables. Models combine components and groups, while drivers run optimization algorithms or design of experiments. Nonlinear and linear solvers can be positioned at different levels of the model hierarchy. Derivative tools include analytic partial derivatives, 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. Dymos for transient modeling and optimal control, and pyCycle for turbine engine cycle analysis, are identified as related libraries. Installation is documented through PyPI or a cloned GitHub repository. The supported OpenMDAO 3.x line requires Python 3.10 or later; its API may change periodically during active development.

Spec sheet

Purpose
OpenMDAO is an open-source Python framework for systems analysis and multidisciplinary optimization.Read 4 Oct 2026 · openmdao.org
Intended users
The project describes applications including cubesat design and mission planning, wind turbine design, and unconventional aircraft concepts.Read 4 Oct 2026 · openmdao.org
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.Read 4 Oct 2026 · openmdao.org
Founded
2007Read 28 Sep 2026 · openmdao.org
Derivative tools
It supports analytic partial derivatives, finite-difference and complex-step approximations, derivative checking, and forward or reverse total derivative calculations.Read 4 Oct 2026 · openmdao.org
Installation
The project documents installation from PyPI or a cloned GitHub repository, with optional dependency sets for testing, documentation, and visualization.Read 4 Oct 2026 · github.com
Model structure
Models are built from components and groups, with drivers that can run optimization algorithms or design of experiments.Read 4 Oct 2026 · openmdao.org
Other optimization
Its parallel computing features can also support gradient-free optimization, mixed-integer nonlinear programming, and design space exploration.Read 4 Oct 2026 · openmdao.org
Parallel computing
MPI features can run parallel subsystems and distributed variables across multiple processes.Read 4 Oct 2026 · openmdao.org
Parallel dependency limit
The documentation says parallel finite-difference and complex-step derivative approximation requires MPI and may not run on Colab or Binder.Read 4 Oct 2026 · openmdao.org
Primary method
The project focuses on gradient-based optimization with analytic derivatives for design spaces with hundreds or thousands of design variables.Read 4 Oct 2026 · openmdao.org
Related libraries
The project identifies Dymos for transient modeling and optimal control and pyCycle for turbine engine cycle analysis as libraries built on OpenMDAO.Read 4 Oct 2026 · openmdao.org
Solver features
OpenMDAO provides nonlinear and linear solvers that can be placed at different levels of a model hierarchy.Read 4 Oct 2026 · openmdao.org
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.Read 4 Oct 2026 · github.com
Visualization and recording
Documented features include model visualizations, optimization progress plots, and recording and reading model or solver cases.Read 4 Oct 2026 · openmdao.org

Plans and prices

OpenMDAO Free open-source framework · Apache 2.0 license Read 4 Oct 2026 · openmdao.org

Every OpenMDAO plan and price →

Strong points and limits

Strong points

  • Free under the Apache 2.0 license
  • Supports analytic and approximate derivative calculations
  • MPI features support parallel subsystems and distributed variables
  • Includes model visualization and case recording
  • Supports gradient-free and mixed-integer optimization

Limits

  • Supported 3.x line requires Python 3.10 or later
  • API may change periodically during active development
  • Some parallel approximations require MPI
  • Parallel derivative approximations may not run on Colab or Binder

Who it suits

OpenMDAO suits engineers and researchers building systems models for optimization, including the listed applications of cubesat design, wind turbine design and unconventional aircraft concepts. It is especially relevant to users working with analytic derivatives or parallel computing.

Verdict

OpenMDAO brings model composition, derivative tools, solvers and parallel features into a free Python framework. Check the Python requirement and MPI limitation against your intended environment, and account for possible API changes.

Where Specifiction places it

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