We develop scientific software for nonlinear optimization, i.e.,
minimization of nonlinear functions subject to nonlinear constraints. An implementation of a sequential quadratic programming (SQP) method
is widely used in industry and academia (NLPQL). Special variants are least squares, data fitting, or nonlinear regression problems, respectively, for which highly efficient numerical algorithms have been implemented together with convenient user interfaces with up to 1,300 test examples. In the most complex case, dynamical systems consist of ordinary or even partial differential equations.
