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)
Abstract:
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