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Merge pull request #147 from simopt-admin/refactor_docs
Update Documentation Structure
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‎.github/workflows/sphinx.yml‎

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name: Sphinx Docs Build
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on:
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push:
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branches: [ "master", "development" ]
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jobs:
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build:
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runs-on: ubuntu-latest
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steps:
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- name: Checkout repository
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uses: actions/checkout@v3
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with:
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fetch-depth: 0
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ref: ${{ github.ref }}
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- name: Set up Python
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uses: actions/setup-python@v4
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with:
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python-version: '3.9'
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- name: Install dependencies
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run: pip install -r docs/requirements.txt
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- name: Build documentation
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run: sphinx-build -b html docs/source docs/_build/html
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- name: Commit and push changes
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run: |
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git config --global user.name "github-actions[bot]"
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git config --global user.email "github-actions[bot]@users.noreply.github.com"
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git add docs/_build/html
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git diff --quiet && echo "No changes to commit" || (git commit -m "Automated documentation update" && git push origin HEAD:${GITHUB_REF#refs/heads/})

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docs/model_template.rst renamed to docs/_templates/model_template.rst

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Model: <model_name> (<model_abbreviation>)
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==========================================
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Description:
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------------
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<A paragraph describing the stochastic model. Use math if it is helpful.>
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Sample math... :math:`S = 1500`
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Sample math...
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.. math::
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\frac{ \sum_{t=0}^{N}f(t,k) }{N}
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Sources of Randomness:
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----------------------
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<The number and nature of sources of randomness.>
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Model Factors:
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--------------
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* <factor1name>: <short description>
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* Default: <default value>
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* <factor2name>: <short description>
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* Default: <default value>
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* <factor3name>: <short description>
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* Default: <default value>
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Responses:
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----------
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* <response1name>: <short description>
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* <response2name>: <short description>
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* <response3name>: <short description>
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References:
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===========
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This model is adapted from the article <article name with full citation + hyperlink to journal/arxiv page>
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Optimization Problem: <problem_name> (<problem_abbrev>)
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========================================================
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Decision Variables:
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-------------------
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* <dv1name that matches model factor name>
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* <dv2name that matches model factor name>
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Objectives:
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-----------
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<Description using response names. Use math if it is helpful.>
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Constraints:
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------------
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<Description using response names. Use math if it is helpful.>
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Problem Factors:
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----------------
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* <factor1name>: <short description>
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* Default: <default value>
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* <factor2name>: <short description>
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* Default: <default value>
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Fixed Model Factors:
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--------------------
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* <factor1name>: <fixed value>
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* <factor2name>: <fixed value>
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Starting Solution:
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------------------
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* <dv1name>: <dv1initialvalue>
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* <dv2name>: <dv2initialvalue>
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Random Solutions:
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------------------
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<description of how to generate random solutions>
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Optimal Solution:
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-----------------
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<if known, otherwise unknown>
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Optimal Objective Function Value:
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---------------------------------
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<if known, otherwise unknown>
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Optimization Problem: <problem_name> (<problem_abbrev>)
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========================================================
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...
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Model: <model_name> (<model_abbreviation>)
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==========================================
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Description:
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------------
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<A paragraph describing the stochastic model. Use math if it is helpful.>
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Sample math... :math:`S = 1500`
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Sample math...
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.. math::
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\frac{ \sum_{t=0}^{N}f(t,k) }{N}
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Sources of Randomness:
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----------------------
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<The number and nature of sources of randomness.>
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Model Factors:
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--------------
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* <factor1name>: <short description>
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* Default: <default value>
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* <factor2name>: <short description>
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* Default: <default value>
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* <factor3name>: <short description>
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* Default: <default value>
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Responses:
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----------
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* <response1name>: <short description>
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* <response2name>: <short description>
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* <response3name>: <short description>
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References:
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===========
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This model is adapted from the article <article name with full citation + hyperlink to journal/arxiv page>
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Optimization Problem: <problem_name> (<problem_abbrev>)
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========================================================
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Decision Variables:
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-------------------
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* <dv1name that matches model factor name>
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* <dv2name that matches model factor name>
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Objectives:
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-----------
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<Description using response names. Use math if it is helpful.>
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Constraints:
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------------
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<Description using response names. Use math if it is helpful.>
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Problem Factors:
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----------------
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* <factor1name>: <short description>
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* Default: <default value>
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* <factor2name>: <short description>
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* Default: <default value>
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Fixed Model Factors:
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--------------------
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* <factor1name>: <fixed value>
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* <factor2name>: <fixed value>
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Starting Solution:
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------------------
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* <dv1name>: <dv1initialvalue>
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* <dv2name>: <dv2initialvalue>
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Random Solutions:
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------------------
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<description of how to generate random solutions>
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Optimal Solution:
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-----------------
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<if known, otherwise unknown>
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Optimal Objective Function Value:
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---------------------------------
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<if known, otherwise unknown>
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Optimization Problem: <problem_name> (<problem_abbrev>)
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========================================================
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...

docs/solver_template.rst renamed to docs/_templates/solver_template.rst

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Solver: <solver_name> (<solver_abbreviation>)
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=============================================
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Description:
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------------
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<A paragraph describing the solver algorithm. Use math if it is helpful.>
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Sample math... :math:`S = 1500`
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Sample math...
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.. math::
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\frac{ \sum_{t=0}^{N}f(t,k) }{N}
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Modifications & Implementation:
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-------------------------------
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<What changed from the original algorithm? Other implementation choices like how initial points are chosen, etc.>
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Scope:
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------
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<The types of models that can be solved (i.e. objective_type, constraint_type, and variable_type).>
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Solver Factors:
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---------------
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* <factor1name>: <short description>
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* Default: <default value>
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* <factor2name>: <short description>
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* Default: <default value>
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* <factor3name>: <short description>
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* Default: <default value>
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References:
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===========
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Solver: <solver_name> (<solver_abbreviation>)
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=============================================
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Description:
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------------
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<A paragraph describing the solver algorithm. Use math if it is helpful.>
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Sample math... :math:`S = 1500`
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Sample math...
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.. math::
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\frac{ \sum_{t=0}^{N}f(t,k) }{N}
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Modifications & Implementation:
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-------------------------------
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<What changed from the original algorithm? Other implementation choices like how initial points are chosen, etc.>
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Scope:
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------
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<The types of models that can be solved (i.e. objective_type, constraint_type, and variable_type).>
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Solver Factors:
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---------------
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* <factor1name>: <short description>
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* Default: <default value>
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* <factor2name>: <short description>
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* Default: <default value>
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* <factor3name>: <short description>
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* Default: <default value>
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References:
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===========
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This solver is adapted from the article <article name with full citation + hyperlink to journal/arxiv page>

docs/GUI.rst renamed to docs/source/GUI.rst

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GUI module
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==========
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.. automodule:: GUI
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:members:
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:undoc-members:
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:show-inheritance:
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GUI module
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==========
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.. automodule:: GUI
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:members:
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:undoc-members:
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:show-inheritance:

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