pyOpt - PYthon OPTimization Framework
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Copyright (c) 2008-2014, pyOpt Developers
pyOpt is an object-oriented framework for formulating and solving
nonlinear constrained optimization problems.
Some of the features of pyOpt:
* Object-oriented development maintains independence between
the optimization problem formulation and its solution by
different optimizers
* Allows for easy integration of gradient-based, gradient-free,
and population-based optimization algorithms
* Interfaces both open source as well as industrial optimizers
* Ease the work required to do nested optimization and provides
automated solution refinement
* On parallel systems it enables the use of optimizers when
running in a mpi parallel environment, allows for evaluation
of gradients in parallel, and can distribute function
evaluations for gradient-free optimizers
* Optimization solution histories can be stored during the
optimization process. A partial history can also be used
to warm-restart the optimization
see the QUICKGUIDE file for further details.
Licensing
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Distributed using the GNU Lesser General Public License (LGPL); see
the LICENSE file for details.
Please cite pyOpt and the authors of the respective optimization
algorithms in any publication for which you find it useful.
(This is not a legal requirement, just a polite request.)
Contact and Feedback
--------------------
If you have questions, comments, problems, want to contribute to the
framework development, or want to report a bug, please contact the
main developers:
* Dr. Ruben E. Perez (Ruben.Perez@rmc.ca)
* Peter W. Jansen (Peter.Jansen@rmc.ca)