ipfilter - an NLP Solver based on a primal-dual interior-point filter algorithm

ipfilter

An NLP Solver based on a primal-dual interior-point filter algorithm

ipfilter is a solver for nonlinear programming problems (defined by the minimization of an objective function in a feasible region defined by equality and inequality constraints).

ipfilter (version 0.3) is written in Fortran 90.
ipfilter provides interfaces to AMPL and SIF and a user 'standard' Fortran interface.
ipfilter is capable of solving large-scale NLPs. The sparse linear algebra uses MA57 from HSL.
Version 0.3 requires first and second-order derivatives for all the functions defining the problem.
The file README.ipfilter contains some information concerning the structure and usage of ipfilter.
Version 0.3 of ipfilter can be obtained by sending e-mail to ipfilter@mat.uc.pt.

ipfilter is freely available for academic purposes (i.e., as a tool for education or for basic research, as well as for benchmarking). We expect that all publications describing work using this software quote the references given below:

M. Ulbrich, S. Ulbrich, and L. N. Vicente, A globally convergent primal-dual interior-point filter method for nonlinear programming, Mathematical Programming, 100 (2004) 379-410 PDF
R. Silva, M. Ulbrich, S. Ulbrich, and L. N. Vicente, A globally convergent primal-dual interior-point filter method for nonlinear programming: new filter optimality measures and computational results, pre-print 08-49, Department of Mathematics, University of Coimbra PDF
test set 1 (old CUTE): list and tar.gz
test set 2 (CUTEr): list

The ipfilter team:
Renata Silva and Luís Nunes Vicente (University of Coimbra)
Michael Ulbrich (Technical University of Munich)
Stefan Ulbrich (Technical University of Darmstadt)