Update references; add DOI

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)
+<a href="https://github.com/ANL-CEEESA/MIPLearn/releases/latest">
+<img src="https://img.shields.io/github/v/release/ANL-CEEESA/MIPLearn">
+</a>
 
 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
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