CasADi
Summary:
CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs.
URL: http://casadi.org
Developers:
- Joel Andersson, Joris Gillis, Greg Horn
| Mode: |
Forward Reverse |
| Method: |
Operator overloading |
| Supported Language: |
C/C++ MATLAB Python |
Reference:
Joel Andersson, Johan \AAkesson, Moritz Diehl
CasADI: A Symbolic Package for Automatic Differentiation and Optimal Control
Recent Advances in Algorithmic Differentiation, Springer, 2012
CasADI: A Symbolic Package for Automatic Differentiation and Optimal Control
Recent Advances in Algorithmic Differentiation, Springer, 2012
Features:
* Matrix-valued expression graphs
* Supports self-contained C-code generation
* Interfaces state-of-the-art codes such as SUNDIALS, IPOPT, SNOPT
* Can be used in Python and Matlab
* Useful as a tool to write your own dynamic optimization solvers
Supported Platforms:
- Windows
- Unix/Linux
- Mac
Licensing: open source
Entries in our publication database that actually use CasADi in the numerical experiments: 5
The following diagram shows these entries versus the year of the publication.
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