NLPQLF: A Fortran Implementation of
a Feasible SQP Method for Solving Nonlinear Constrained Optimization Problems -
User's Guide, Version 2.0
K. Schittkowski, Report, Department of Computer Science, University of Bayreuth (2009)
The Fortran subroutine NLPQLF solves smooth nonlinear programming problems and is an extension of the code NLPQLP. It is assumed that objective function or constraints can be evaluated only at argument values from a convex set described by some other inequality constraints. The numerical method performs a two-stage process. Starting from a point feasible subject to these 'simple' constraints, a new search direction is computed by solving a quadratic program expanded by the nonlinear feasibility constraints. Thus, the new iterate is feasible subject to these constraints and objective function as well as the remaining constraint function values can be evaluated. The usage of the code is documented and illustrated by an example.
To download the report, click here: NLPQLF.pdf