Here you can find an alphabetical list of software packages that is being co-developed and/or maintained by members of the Institute for Mathematical Optimization.
You can find an additional selection of software packages in our GitLab Repository
ISPoc (Intrusive Spectral Projection for optimal control) is a framework for transforming uncertain optimal control problems into deterministic surrogates, which can be solved with a direct method for optimal control (MUSCOD-II). It contains a symbolic implementation of the intrusive spectral projections method (Polynomial Chaos expansion).
(with Simulation & Optimization group at IWR Heidelberg)
Our in-house mixed-integer optimal control software package MUSCOD-II now has an AMPL interface that allows to model DAE-constrained optimal control problems in AMPL.
A python package that computes Irreducible Infeasible Subsystem Arc Covers in Flow Networks; included is a generator for infeasible network flow problems.
pySLEQP is a prototypical implementation of a nonlinear programming solver employing a sequential linear equality constrained quadratic programming method.
(with H.J. Ferreau at ABB Baden/Switzerland, A. Potschka at IWR Heidelberg)
qpOASES is a primal-dual active set code for dense and sparse parametric QPs. It is well suited for hot-starting when solving a sequence of related QPs, such as in model predictive control or sequential quadratic programming. qpOASES is now hosted by the COIN-OR foundation and is available for free under the GNU LGPL license.
SCARP is a code computing solution to mixed-integer optimal control problems. It computes solutions by rounding solutions of fractional relaxations while taking switching costs into account, enabling the penalization of chattering, extending previous modeling capabilities.
SCIP is a Branch-and-Cut framework and also contains a fast integer optimization solver. SCIP is developed together with the Zuse Institute Berlin and the Universitity of Erlangen-Nürnberg, Chair of EDOM.
SoPlex is a fast linear optimization solver. SoPlex is developed together with the Zuse Institute Berlin.
(with S. Leyffer at Argonne National Labs)
TACO is the Toolkit for AMPL Control Optimization that drives MUSCOD-II on NEOS. It defines some add-ons to the AMPL modeling language that allow the elegant formulation of ODE/DAE optimal control problems in AMPL. Developers of optimal control problem solvers may want to take a look at the TACO source code to interface their solvers with AMPL.
(with Felix Lenders, Andreas Potschka at IWR Heidelberg)
This is a library that provides various methods related to solving the trust region subproblem in an iterative way. The principal approach follows the GLTR method by N. Gould.
trlib is now part of SciPy and can be called via scipy.optimize.minimize.