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Remove references to projects.coin-or.org #3612

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2 changes: 1 addition & 1 deletion doc/OnlineDocs/explanation/analysis/parmest/installation.rst
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Expand Up @@ -21,7 +21,7 @@ Python package dependencies
IPOPT
-----

IPOPT can be downloaded from https://projects.coin-or.org/Ipopt.
The IPOPT project homepage is https://github.com/coin-or/Ipopt

Testing
-------
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4 changes: 2 additions & 2 deletions doc/OnlineDocs/explanation/analysis/sensitivity_toolbox.rst
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Expand Up @@ -3,7 +3,7 @@ Sensitivity Toolbox

The sensitivity toolbox provides a Pyomo interface to sIPOPT and k_aug to very quickly compute approximate solutions to nonlinear programs with a small perturbation in model parameters.

See the `sIPOPT documentation <https://projects.coin-or.org/Ipopt/wiki/sIpopt>`_ or the `following paper <https://link.springer.com/article/10.1007/s12532-012-0043-2>`_ for additional details:
See the `sIPOPT documentation <https://coin-or.github.io/Ipopt/SPECIALS.html#SIPOPT>`_ or the `following paper <https://link.springer.com/article/10.1007/s12532-012-0043-2>`_ for additional details:

H. Pirnay, R. Lopez-Negrete, and L.T. Biegler, Optimal Sensitivity based on IPOPT, Math. Prog. Comp., 4(4):307--331, 2012.

Expand Down Expand Up @@ -185,7 +185,7 @@ Installing sIPOPT and k_aug
The sensitivity toolbox requires either sIPOPT or k_aug to be installed and available in your system PATH. See the sIPOPT and k_aug documentation for detailed instructions:

* https://coin-or.github.io/Ipopt/INSTALL.html
* https://projects.coin-or.org/Ipopt/wiki/sIpopt
* https://coin-or.github.io/Ipopt/SPECIALS.html#SIPOPT
* https://coin-or.github.io/coinbrew/
* https://github.com/dthierry/k_aug

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2 changes: 1 addition & 1 deletion examples/doc/samples/case_studies/rosen/Rosenbrock.output
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Expand Up @@ -7,7 +7,7 @@ Ipopt 3.9.2:
******************************************************************************
This program contains Ipopt, a library for large-scale nonlinear optimization.
Ipopt is released as open source code under the Eclipse Public License (EPL).
For more information visit http://projects.coin-or.org/Ipopt
For more information visit https://github.com/coin-or/Ipopt
******************************************************************************

This is Ipopt version 3.9.2, running with linear solver ma27.
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2 changes: 1 addition & 1 deletion examples/pyomo/suffixes/ipopt_warmstart.py
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Expand Up @@ -11,7 +11,7 @@

# A Suffix example for ipopt.
# Translated to Pyomo from AMPL model source at:
# https://projects.coin-or.org/Ipopt/wiki/IpoptAddFeatures
# http://web.archive.org/web/20120610123756/https://projects.coin-or.org/Ipopt/wiki/IpoptAddFeatures
#
# This Pyomo example is formulated as a python script.
# To run this script execute the following command:
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5 changes: 5 additions & 0 deletions pyomo/contrib/sensitivity_toolbox/sens.py
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Expand Up @@ -214,6 +214,11 @@ def sensitivity_calculation(
sens.perturb_parameters(perturbList)

if method == 'sipopt':
# Notes on sIpopt documentation:
# Documentation:
# - https://coin-or.github.io/Ipopt/SPECIALS.html#SIPOPT
# Original docs (archived):
# - http://web.archive.org/web/20210412132144/https://projects.coin-or.org/Ipopt/wiki/sIpopt
ipopt_sens = SolverFactory('ipopt_sens', solver_io='nl')
ipopt_sens.options['run_sens'] = 'yes'
if solver_options is not None:
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12 changes: 7 additions & 5 deletions pyomo/contrib/solver/tests/solvers/test_ipopt.py
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Expand Up @@ -154,12 +154,14 @@ def test_version_cache(self):

def test_parse_output(self):
# Old ipopt style (<=3.13)
output = """Ipopt 3.13.2:
# Note: we are removing the URLs from the baseline because they
# do not impact the test (and checking the URLs is fragile)
output = """Ipopt 3.13.2:

******************************************************************************
This program contains Ipopt, a library for large-scale nonlinear optimization.
Ipopt is released as open source code under the Eclipse Public License (EPL).
For more information visit http://projects.coin-or.org/Ipopt
For more information visit
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Honestly it might be better to remove all of the top part and just leave the "actual data" section, but it's fine either way.


This version of Ipopt was compiled from source code available at
https://github.com/IDAES/Ipopt as part of the Institute for the Design of
Expand All @@ -171,7 +173,7 @@ def test_parse_output(self):
publicity material resulting from use of the HSL codes within IPOPT must
contain the following acknowledgement:
HSL, a collection of Fortran codes for large-scale scientific
computation. See http://www.hsl.rl.ac.uk.
computation. See
******************************************************************************

This is Ipopt version 3.13.2, running with linear solver ma27.
Expand Down Expand Up @@ -226,7 +228,7 @@ def test_parse_output(self):
Total CPU secs in NLP function evaluations = 0.000

EXIT: Optimal Solution Found.

"""
parsed_output = ipopt.Ipopt()._parse_ipopt_output(output)
self.assertEqual(parsed_output["iters"], 11)
Expand All @@ -241,7 +243,7 @@ def test_parse_output(self):
output = """******************************************************************************
This program contains Ipopt, a library for large-scale nonlinear optimization.
Ipopt is released as open source code under the Eclipse Public License (EPL).
For more information visit https://github.com/coin-or/Ipopt
For more information visit
******************************************************************************

This is Ipopt version 3.14.17, running with linear solver ma27.
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