Bibliography

1
L. T. Biegler.
Nonlinear Programming: Concepts, Algorithms and Applications to Chemical Processes
SIAM, Philadelphia (2010)

2
F. E. Curtis, J. Huber, O. Schenk, A. Wächter.
A note on the implementation of an interior-point algorithm for nonlinear optimization with inexact step computations.
Mathematical Programming, 136(1):209-227, 2012
doi: 10.1007/s10107-012-0557-4.
preprint at http://www.optimization-online.org/DB_HTML/2011/04/2992.html

3
R. Fourer, D. M. Gay, and B. W. Kernighan.
AMPL: A Modeling Language For Mathematical Programming.
Thomson Publishing Company, Danvers, MA, USA, 1993.

4
O. Schenk, A. Wächter, and M. Hagemann.
Matching-based preprocessing algorithms to the solution of saddle-point problems in large-scale nonconvex interior-point optimization.
Computational Optimization Applications, 36(2-3):321-341, 2007
doi: 10.1007/s10589-006-9003-y.

5
W. Hock and K. Schittkowski.
Test examples for nonlinear programming codes.
Lecture Notes in Economics and Mathematical Systems, 187, 1981.
doi: 10.1007/978-3-642-48320-2.

6
J. Nocedal, A. Wächter, and R. A. Waltz.
Adaptive barrier strategies for nonlinear interior methods.
SIAM Journal on Optimization, 19(4):1674-1693, 2008.
doi: 10.1137/060649513.
preprint at http://www.optimization-online.org/DB_HTML/2005/03/1089.html

7
H. Pirnay, R. López-Negrete, and L. T. Biegler.
Optimal Sensitivity based on IPOPT.
Mathematical Programming Computations, 4(4):307-331, 2012.
doi: 10.1007/s12532-012-0043-2.
preprint at http://www.optimization-online.org/DB_HTML/2011/04/3008.html

8
A. Wächter.
An Interior Point Algorithm for Large-Scale Nonlinear Optimization with Applications in Process Engineering.
PhD thesis, Carnegie Mellon University, Pittsburgh, PA, USA, January 2002.
available at http://researcher.watson.ibm.com/researcher/files/us-andreasw/thesis.pdf

9
A. Wächter.
Short Tutorial: Getting Started With Ipopt in 90 Minutes.
In Combinatorial Scientific Computing (U. Naumann, O. Schenk, H. D. Simon, eds.), 2009.
urn: nbn:de:0030-drops-20890

10
A. Wächter and L. T. Biegler.
Line search filter methods for nonlinear programming: Local convergence.
SIAM Journal on Optimization, 16(1):32-48, 2005.
doi: 10.1137/S1052623403426544

11
A. Wächter and L. T. Biegler.
Line search filter methods for nonlinear programming: Motivation and global convergence.
SIAM Journal on Optimization, 16(1):1-31, 2005.
doi: 10.1137/S1052623403426556

12
A. Wächter and L. T. Biegler.
Global and Local Convergence of Line Search Filter Methods for Nonlinear Programming.
Optimization Online, 2001.
http://www.optimization-online.org/DB_HTML/2001/08/367.html

13
A. Wächter and L. T. Biegler.
On the implementation of a primal-dual interior point filter line search algorithm for large-scale nonlinear programming.
Mathematical Programming, 106(1):25-57, 2006.
doi: 10.1007/s10107-004-0559-y.
preprint at http://www.optimization-online.org/DB_HTML/2004/03/836.html

14
V. M. Zavala and N. Chiang.
An Inertia-free Filter Line-search Algorithm for Large-scale Nonlinear Programming.
Preprint ANL/MCS-P5197-0914, Argonne National Laboratory, 2014.