From 87a89eaf964683a28b62a9c4d32c225cc1823cac Mon Sep 17 00:00:00 2001 From: "Alinson S. Xavier" Date: Thu, 3 Dec 2020 12:21:27 -0600 Subject: [PATCH] Update references; add DOI --- README.md | 20 +++++++++++++++++++- docs/about.md | 11 +++++++++-- 2 files changed, 28 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index d64b4b0..5c60afc 100644 --- a/README.md +++ b/README.md @@ -1,5 +1,8 @@ ![Build status](https://img.shields.io/github/workflow/status/ANL-CEEESA/MIPLearn/Test) -![BSD License](https://img.shields.io/badge/license-BSD-blue) +[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.4287567.svg)](https://doi.org/10.5281/zenodo.4287567) + + + MIPLearn ======== @@ -23,6 +26,21 @@ Documentation For installation instructions, basic usage and benchmarks results, see the [official documentation](https://anl-ceeesa.github.io/MIPLearn/). +Acknowledgments +--------------- +* 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. + +Citing MIPLearn +--------------- + +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: + +* **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) + +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: + +* **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) + License ------- diff --git a/docs/about.md b/docs/about.md index cc5d7db..ba091a7 100644 --- a/docs/about.md +++ b/docs/about.md @@ -7,11 +7,18 @@ ### Acknowledgments -* 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. +* 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. ### References -* **Learning to Solve Large-Scale Security-Constrained Unit Commitment Problems.** *Alinson S. Xavier, Feng Qiu, Shabbir Ahmed*. INFORMS Journal on Computing (to appear). [ArXiv:1902:01696](https://arxiv.org/abs/1902.01697) + +If you use MIPLearn in your research, or the included problem generators, we kindly request that you cite the package as follows: + +* **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) + +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: + +* **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) ### License