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59 lines
2.9 KiB
59 lines
2.9 KiB
```{sectnum}
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---
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start: 4
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depth: 2
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suffix: .
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---
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```
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# About
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## Authors
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* **Alinson S. Xavier,** Argonne National Laboratory <<axavier@anl.gov>>
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* **Feng Qiu,** Argonne National Laboratory <<fqiu@anl.gov>>
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## Acknowledgments
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* Based upon work supported by **Laboratory Directed Research and Development** (LDRD) funding from Argonne National Laboratory, provided by the Director, Office of Science, of the U.S. Department of Energy under Contract No. DE-AC02-06CH11357, and the **U.S. Department of Energy Advanced Grid Modeling Program** under Grant DE-OE0000875.
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## References
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If you use MIPLearn in your research, or the included problem generators, we kindly request that you cite the package as follows:
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* **Alinson S. Xavier, Feng Qiu.** *MIPLearn: An Extensible Framework for Learning-Enhanced Optimization*. Zenodo (2020). 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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* **Alinson S. Xavier, Feng Qiu, Shabbir Ahmed.** *Learning to Solve Large-Scale Unit Commitment Problems.* INFORMS Journal on Computing (2020). DOI: [10.1287/ijoc.2020.0976](https://doi.org/10.1287/ijoc.2020.0976)
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## License
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```text
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MIPLearn, an extensible framework for Learning-Enhanced Mixed-Integer Optimization
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Copyright © 2020, UChicago Argonne, LLC. All Rights Reserved.
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Redistribution and use in source and binary forms, with or without modification, are permitted
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provided that the following conditions are met:
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1. Redistributions of source code must retain the above copyright notice, this list of
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conditions and the following disclaimer.
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2. Redistributions in binary form must reproduce the above copyright notice, this list of
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conditions and the following disclaimer in the documentation and/or other materials provided
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with the distribution.
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3. Neither the name of the copyright holder nor the names of its contributors may be used to
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endorse or promote products derived from this software without specific prior written
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permission.
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THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR
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IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY
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AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR
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CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
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SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
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THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
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OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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POSSIBILITY OF SUCH DAMAGE.
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```
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