The TOMLAB /NPSOL toolbox efficiently integrates well-known solvers developed by the Stanford Systems Optimization Laboratory (SOL) with Matlab and TOMLAB.

The toolbox includes:

• 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 /NPSOL User's Guide.
• TOMLAB /NPSOL includes all Matlab code and solvers that are part of TOMLAB /MINOS, see the description of TOMLAB /MINOS.
   

Main features

• The codes are implemented to efficiently handle Matlab sparse arrays.
   
• It is easy to use warm starts for the solvers, and further speed up sequences of optimization problems.
   
• NPSOL has been used intensively in control applications because of its speed and robustness.
   
• LSSOL, NPSOL and NLSSOL all may be used as sub problem solvers for other TOMLAB solvers.
   
• NPSOL and NLSSOL may estimate derivatives internally, faster than using one of the six TOMLAB methods.