A C/C++ implementation of the MST2 multistart tabu search algorithm for quadratic unconstrained binary optimization (QUBO) problems with a dimod sampler Python interface.
Install from a wheel on PyPI:
pip install dwave-tabu
Alternatively, you can build the library with setuptools. This build requires that your system has a C++ compiler toolchain installed, as well as SWIG.
pip install -r requirements.txt
python setup.py build_ext --inplace
python setup.py install
This example solves a two-variable Ising model.
>>> from tabu import TabuSampler
>>> response = TabuSampler().sample_ising({'a': -0.5, 'b': 1.0}, {('a', 'b'): -1})