The TOMLAB /SOL toolbox efficiently integrates all well-known solvers developed by the Stanford
Systems Optimization Laboratory (SOL) with Matlab and TOMLAB.
The toolbox includes
The sparse general nonlinear solver SNOPT,
The sparse positive convex quadratic solver SQOPT,
The dense general constrained nonlinear solver NPSOL,
The dense constrained linear least squares and convex quadratic program
solver LSSOL and
The dense constrained nonlinear least squares solver NLSSOL, based on NPSOL.
- Read more about the above mentioned SOL solvers, as well as the TOMLAB /MINOS solvers MINOS, QPOPT and LPOPT in the TOMLAB /SOL User's Guide.
TOMLAB /SOL includes all Matlab code and solvers that are
part of TOMLAB /MINOS,
see the description of
For a general description of the TOMLAB features, see
The codes are implemented to
efficiently handle Matlab sparse arrays.
It is easy to use warm starts for the SOL solvers,
and further speed up sequences of
NPSOL has been used intensively in control applications because
of its speed and robustness.
All SOL solvers may be used as sub problem solvers for other
NPSOL and SNOPT may estimate derivatives internally, faster than
using one of the six TOMLAB methods.