diff --git a/doc/OnlineDocs/explanation/analysis/parmest/installation.rst b/doc/OnlineDocs/explanation/analysis/parmest/installation.rst index 0cba08039ce..5cc41878719 100644 --- a/doc/OnlineDocs/explanation/analysis/parmest/installation.rst +++ b/doc/OnlineDocs/explanation/analysis/parmest/installation.rst @@ -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 ------- diff --git a/doc/OnlineDocs/explanation/analysis/sensitivity_toolbox.rst b/doc/OnlineDocs/explanation/analysis/sensitivity_toolbox.rst index f0069565ff6..b4c9088e81b 100644 --- a/doc/OnlineDocs/explanation/analysis/sensitivity_toolbox.rst +++ b/doc/OnlineDocs/explanation/analysis/sensitivity_toolbox.rst @@ -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 `_ or the `following paper `_ for additional details: +See the `sIPOPT documentation `_ or the `following paper `_ 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. @@ -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 diff --git a/examples/doc/samples/case_studies/rosen/Rosenbrock.output b/examples/doc/samples/case_studies/rosen/Rosenbrock.output index 0373812083e..c8fa0a5732a 100644 --- a/examples/doc/samples/case_studies/rosen/Rosenbrock.output +++ b/examples/doc/samples/case_studies/rosen/Rosenbrock.output @@ -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. diff --git a/examples/pyomo/suffixes/ipopt_warmstart.py b/examples/pyomo/suffixes/ipopt_warmstart.py index a8ade973004..6190f3ab849 100644 --- a/examples/pyomo/suffixes/ipopt_warmstart.py +++ b/examples/pyomo/suffixes/ipopt_warmstart.py @@ -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: diff --git a/pyomo/contrib/sensitivity_toolbox/sens.py b/pyomo/contrib/sensitivity_toolbox/sens.py index c1cd82a15b7..22ed7486311 100644 --- a/pyomo/contrib/sensitivity_toolbox/sens.py +++ b/pyomo/contrib/sensitivity_toolbox/sens.py @@ -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: diff --git a/pyomo/contrib/solver/tests/solvers/test_ipopt.py b/pyomo/contrib/solver/tests/solvers/test_ipopt.py index 38510dbdf44..226e6b2a614 100644 --- a/pyomo/contrib/solver/tests/solvers/test_ipopt.py +++ b/pyomo/contrib/solver/tests/solvers/test_ipopt.py @@ -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 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 @@ -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. @@ -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) @@ -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.