Description
Sparse nonlinear optimization problems can be solved with tools aimed at scientific and engineering models.
It is useful for researchers and engineers working with constrained optimization, simulation, or control problems. Numerical solvers depend on model formulation, tolerances, scaling, and validation against known results.