Metadata-Version: 2.1
Name: MQLib
Version: 0.1
Summary: Heuristics for the Max-cut and QUBO combinatorial optimization problems
Home-page: https://github.com/MQLib/MQLib
Author: Iain Dunning, Swati Gupta, and John Silberholz
Author-email: john.silberholz@gmail.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: C++
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.5
Description-Content-Type: text/markdown
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: networkx


Python interface to the MQLib, a C++ library of heuristics for Max-Cut
and Quadratic Unconstrained Binary Optimization (QUBO). Also includes a
hyperheuristic, which uses machine learning to predict the best-performing
heuristic for a given problem instance and then runs that heuristic.

This library and the related systematic heuristic evaluation strategy are described in [the paper](https://github.com/MQLib/MQLib/blob/master/paper/SECM_final.pdf). To cite the MQLib, please use:
```
@article{DunningEtAl2018,
  title={What Works Best When? A Systematic Evaluation of Heuristics for Max-Cut and {QUBO}},
  author={Dunning, Iain and Gupta, Swati and Silberholz, John},
  year={2018},
  journal={{INFORMS} Journal on Computing},
  volume={30},
  number={3}
}
```


