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Bump version to 0.4
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Makefile

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@@ -3,7 +3,7 @@ PYTEST := pytest
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PIP := $(PYTHON) -m pip
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MYPY := $(PYTHON) -m mypy
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PYTEST_ARGS := -W ignore::DeprecationWarning -vv --log-level=DEBUG
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VERSION := 0.3
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VERSION := 0.4
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all: docs test
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README.md

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-------------
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- Tutorials:
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1. [Getting started (Pyomo)](https://anl-ceeesa.github.io/MIPLearn/0.3/tutorials/getting-started-pyomo/)
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2. [Getting started (Gurobipy)](https://anl-ceeesa.github.io/MIPLearn/0.3/tutorials/getting-started-gurobipy/)
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3. [Getting started (JuMP)](https://anl-ceeesa.github.io/MIPLearn/0.3/tutorials/getting-started-jump/)
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1. [Getting started (Pyomo)](https://anl-ceeesa.github.io/MIPLearn/0.4/tutorials/getting-started-pyomo/)
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2. [Getting started (Gurobipy)](https://anl-ceeesa.github.io/MIPLearn/0.4/tutorials/getting-started-gurobipy/)
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3. [Getting started (JuMP)](https://anl-ceeesa.github.io/MIPLearn/0.4/tutorials/getting-started-jump/)
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4. [User cuts and lazy constraints](https://anl-ceeesa.github.io/MIPLearn/0.4/tutorials/cuts-gurobipy/)
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- User Guide
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1. [Benchmark problems](https://anl-ceeesa.github.io/MIPLearn/0.3/guide/problems/)
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2. [Training data collectors](https://anl-ceeesa.github.io/MIPLearn/0.3/guide/collectors/)
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3. [Feature extractors](https://anl-ceeesa.github.io/MIPLearn/0.3/guide/features/)
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4. [Primal components](https://anl-ceeesa.github.io/MIPLearn/0.3/guide/primal/)
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5. [Learning solver](https://anl-ceeesa.github.io/MIPLearn/0.3/guide/solvers/)
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1. [Benchmark problems](https://anl-ceeesa.github.io/MIPLearn/0.4/guide/problems/)
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2. [Training data collectors](https://anl-ceeesa.github.io/MIPLearn/0.4/guide/collectors/)
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3. [Feature extractors](https://anl-ceeesa.github.io/MIPLearn/0.4/guide/features/)
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4. [Primal components](https://anl-ceeesa.github.io/MIPLearn/0.4/guide/primal/)
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5. [Learning solver](https://anl-ceeesa.github.io/MIPLearn/0.4/guide/solvers/)
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- Python API Reference
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1. [Benchmark problems](https://anl-ceeesa.github.io/MIPLearn/0.3/api/problems/)
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2. [Collectors & extractors](https://anl-ceeesa.github.io/MIPLearn/0.3/api/collectors/)
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3. [Components](https://anl-ceeesa.github.io/MIPLearn/0.3/api/components/)
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4. [Solvers](https://anl-ceeesa.github.io/MIPLearn/0.3/api/solvers/)
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5. [Helpers](https://anl-ceeesa.github.io/MIPLearn/0.3/api/helpers/)
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1. [Benchmark problems](https://anl-ceeesa.github.io/MIPLearn/0.4/api/problems/)
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2. [Collectors & extractors](https://anl-ceeesa.github.io/MIPLearn/0.4/api/collectors/)
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3. [Components](https://anl-ceeesa.github.io/MIPLearn/0.4/api/components/)
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4. [Solvers](https://anl-ceeesa.github.io/MIPLearn/0.4/api/solvers/)
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5. [Helpers](https://anl-ceeesa.github.io/MIPLearn/0.4/api/helpers/)
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Authors
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-------
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If you use MIPLearn in your research (either the solver or the included problem generators), we kindly request that you cite the package as follows:
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* **Alinson S. Xavier, Feng Qiu, Xiaoyi Gu, Berkay Becu, Santanu S. Dey.** *MIPLearn: An Extensible Framework for Learning-Enhanced Optimization (Version 0.3)*. Zenodo (2023). DOI: [10.5281/zenodo.4287567](https://doi.org/10.5281/zenodo.4287567)
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* **Alinson S. Xavier, Feng Qiu, Xiaoyi Gu, Berkay Becu, Santanu S. Dey.** *MIPLearn: An Extensible Framework for Learning-Enhanced Optimization (Version 0.4)*. Zenodo (2024). DOI: [10.5281/zenodo.4287567](https://doi.org/10.5281/zenodo.4287567)
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If you use MIPLearn in the field of power systems optimization, we kindly request that you cite the reference below, in which the main techniques implemented in MIPLearn were first developed:
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