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
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The sparse general nonlinear solver SNOPT,
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The sparse positive convex quadratic solver SQOPT,
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The dense general constrained nonlinear solver DNOPT,
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The dense general constrained nonlinear solver NPSOL,
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The dense constrained linear least squares and convex quadratic program
solver LSSOL and
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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.
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TOMLAB /SOL includes all Matlab code and solvers that are
part of TOMLAB /MINOS,
see the description of
TOMLAB /MINOS.
-
For a general description of the TOMLAB features, see
the
TOMLAB FEATURES.
Main features
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The codes are implemented to
efficiently handle Matlab sparse arrays.
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It is easy to use warm starts for the SOL solvers,
and further speed up sequences of
optimization problems.
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NPSOL has been used intensively in control applications because
of its speed and robustness.
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All SOL solvers may be used as sub problem solvers for other
TOMLAB solvers.
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DNOPT, NPSOL and SNOPT may estimate derivatives internally, faster than
using one of the six TOMLAB methods.