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Merge pull request #3968 from jsiirola/scip-urls
Remove references to `scipopt.org`; update DoE paper reference
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.github/workflows/test_branches.yml

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# Exclude:
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# - Jenkins because it's behind a firewall
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# - RTD because a magically-generated string triggers failures
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exclude_urls: https://pyomo-jenkins.sandia.gov/,https://pyomo.readthedocs.io/en/%s/errors.html
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# - scipopt.org as they perform "validation" on the webclient (which fails)
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exclude_urls: https://pyomo-jenkins.sandia.gov/,https://pyomo.readthedocs.io/en/%s/errors.html,https://www.scipopt.org
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# Exclude:
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# - All gnu.org links because they consistently fail the checker
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# - All lpsolve.sourceforge.net links because SF appears to reject from GHA

.github/workflows/test_pr_and_main.yml

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# Exclude:
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# - Jenkins because it's behind a firewall
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# - RTD because a magically-generated string triggers failures
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exclude_urls: https://pyomo-jenkins.sandia.gov/,https://pyomo.readthedocs.io/en/%s/errors.html
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# - scipopt.org as they perform "validation" on the webclient (which fails)
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exclude_urls: https://pyomo-jenkins.sandia.gov/,https://pyomo.readthedocs.io/en/%s/errors.html,https://www.scipopt.org
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# Exclude:
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# - All gnu.org links because they consistently fail the checker
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# - All lpsolve.sourceforge.net links because SF appears to reject from GHA

.github/workflows/url_check.yml

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# Exclude:
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# - Jenkins because it's behind a firewall
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# - RTD because a magically-generated string triggers failures
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exclude_urls: https://pyomo-jenkins.sandia.gov/,https://pyomo.readthedocs.io/en/%s/errors.html
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# - scipopt.org as they perform "validation" on the webclient (which fails)
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exclude_urls: https://pyomo-jenkins.sandia.gov/,https://pyomo.readthedocs.io/en/%s/errors.html,https://www.scipopt.org
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# Exclude:
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# - All gnu.org links because they consistently fail the checker
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# - All lpsolve.sourceforge.net links because SF appears to reject from GHA

doc/OnlineDocs/explanation/analysis/doe/doe.rst

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@@ -15,11 +15,10 @@ Significant improvements and extensions were contributed by **Dan Laky**, and
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`Process Optimization & Modeling for Minerals Sustainability (PrOMMiS) <https://www.netl.doe.gov/prommis>`_ project
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and the `University of Notre Dame <https://www.nd.edu/>`_.
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If you use Pyomo.DoE, please cite:
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[Wang and Dowling, 2022] Wang, Jialu, and Alexander W. Dowling.
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"Pyomo.DOE: An open‐source package for model‐based design of experiments in Python."
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AIChE Journal 68.12 (2022): e17813. `https://doi.org/10.1002/aic.17813`
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If you use Pyomo.DoE, please cite the [PyomoDOE-paper]_:
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Wang, Jialu, and Alexander W. Dowling. "Pyomo.DOE: An open‐source
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package for model‐based design of experiments in Python", *AIChE Journal*,
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68(12), e17813. 2022. DOI `10.1002/aic.17813 <https://doi.org/10.1002/aic.17813>`_
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Index of Pyomo.DoE documentation
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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abstraction.rst
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objective.rst
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multexp.rst
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uncertainty.rst
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uncertainty.rst

doc/OnlineDocs/explanation/analysis/doe/guide.rst

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An example of the subclassed :class:`Experiment` object that builds and labels the model is shown in the next few sections.
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This guide illustrates the use of Pyomo.DoE using a reaction kinetics example ([WD22]_).
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This guide illustrates the use of Pyomo.DoE using a reaction kinetics
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example ([PyomoDOE-paper]_).
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.. math::
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:nowrap:

doc/OnlineDocs/explanation/analysis/doe/overview.rst

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A confidence ellipse is a geometric representation of the uncertainty in parameter
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estimates. It is derived from the covariance matrix :math:`\mathbf{V}`.
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In order to solve problems of the above, Pyomo.DoE implements the 2-stage stochastic program. Please see [WD22]_ for details.
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In order to solve problems of the above, Pyomo.DoE implements the
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2-stage stochastic program. Please see [PyomoDOE-paper]_ for details.

doc/OnlineDocs/explanation/solvers/mindtpy.rst

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Global Outer-Approximation
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^^^^^^^^^^^^^^^^^^^^^^^^^^
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Apart from the decomposition methods for convex MINLP problems [`Kronqvist et al., 2019`_], MindtPy provides an implementation of Global Outer Approximation (GOA) as described in [`Kesavan & Allgor, 2004`_], to provide optimality guaranteed for nonconvex MINLP problems. Here, the validity of the Mixed-integer Linear Programming relaxation of the original problem is guaranteed via the usage of Generalized McCormick envelopes, computed using the :ref:`interface to the MC++ package <MC++>`. The NLP subproblems, in this case, need to be solved to global optimality, which can be achieved through global NLP solvers such as `BARON`_ or `SCIP`_.
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.. _BARON: https://minlp.com/baron-solver
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.. _SCIP: https://www.scipopt.org/
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Apart from the decomposition methods for convex MINLP problems [`Kronqvist et al., 2019`_], MindtPy provides an implementation of Global Outer Approximation (GOA) as described in [`Kesavan & Allgor, 2004`_], to provide optimality guaranteed for nonconvex MINLP problems. Here, the validity of the Mixed-integer Linear Programming relaxation of the original problem is guaranteed via the usage of Generalized McCormick envelopes, computed using the :ref:`interface to the MC++ package <MC++>`. The NLP subproblems, in this case, need to be solved to global optimality, which can be achieved through global NLP solvers such as `BARON <https://minlp.com/baron-solver>`__ or `SCIP <https://www.scipopt.org>`__.
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Convergence

doc/OnlineDocs/explanation/solvers/pyros/getting_started.rst

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In advance of using PyROS to solve robust optimization problems,
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you will need (at least) one local nonlinear programming (NLP) solver
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(e.g.,
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`CONOPT <https://conopt.gams.com/>`_,
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`IPOPT <https://github.com/coin-or/Ipopt>`_,
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`Knitro <https://www.artelys.com/solvers/knitro/>`_)
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`CONOPT <https://conopt.gams.com/>`__,
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`IPOPT <https://github.com/coin-or/Ipopt>`__,
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`Knitro <https://www.artelys.com/solvers/knitro/>`__)
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and (at least) one global NLP solver
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(e.g.,
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`BARON <https://minlp.com/baron-solver>`_,
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`COUENNE <https://www.coin-or.org/Couenne/>`_,
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`SCIP <https://www.scipopt.org/>`_)
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`BARON <https://minlp.com/baron-solver>`__,
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`COUENNE <https://www.coin-or.org/Couenne/>`__,
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`SCIP <https://www.scipopt.org>`__)
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installed and licensed on your system.
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PyROS can be installed as follows:
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Some tests involving deterministic NLP solvers may be skipped
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if
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`IPOPT <https://github.com/coin-or/Ipopt>`_,
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`BARON <https://minlp.com/baron-solver>`_,
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`IPOPT <https://github.com/coin-or/Ipopt>`__,
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`BARON <https://minlp.com/baron-solver>`__,
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or
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`SCIP <https://www.scipopt.org/>`_
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`SCIP <https://www.scipopt.org>`__
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is not
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pre-installed and licensed on your system.
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doc/OnlineDocs/getting_started/solvers.rst

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* - SCIP (Command-line)
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- N/A
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- ``conda install ‑c conda‑forge scip``
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- `License <https://www.scipopt.org/scip/doc/html/LICENSE.php>`__
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`Docs <https://www.scipopt.org/index.php#download>`__
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- (see `SCIP <https://www.scipopt.org>`__ project)
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* - SCIP (Python)
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- ``pip install pyscipopt``
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- ``conda install ‑c conda‑forge pyscipopt``
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- `License <https://www.scipopt.org/scip/doc/html/LICENSE.php>`__
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`Docs <https://www.scipopt.org/index.php#download>`__
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- (see `SCIP <https://www.scipopt.org>`__ project)
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* - XPRESS
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- ``pip install xpress``
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- ``conda install ‑c fico‑xpress xpress``

doc/OnlineDocs/reference/bibliography.rst

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and algebraic equations", *Mathematical Programming Computation*, 10(2),
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187-223. 2018.
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.. [PyomoDOE-paper] Wang, Jialu, and Alexander W. Dowling. "Pyomo.DOE: An open‐source
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package for model‐based design of experiments in Python", *AIChE Journal*,
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68(12), e17813. 2022. DOI `10.1002/aic.17813 <https://doi.org/10.1002/aic.17813>`_
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.. [Parmest-paper] Katherine A. Klise, Bethany L. Nicholson, Andrea
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Staid, David L.Woodruff. "Parmest: Parameter Estimation Via Pyomo."
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*Computer Aided Chemical Engineering*, 47, 41-46. 2019.
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.. [NW99] Nocedal, Jorge, and Stephen J. Wright, eds. Numerical
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optimization. New York, NY: Springer New York, 1999.
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.. [WD22] Wang, Jialu, and Alexander W. Dowling. "Pyomo.DOE: An open‐source
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package for model‐based design of experiments in Python", *AIChE Journal*,
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68(12), e17813. 2022. DOI `10.1002/aic.17813Y <https://doi.org/10.1002/aic.17813Y>`_

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