In general, TensorFlow and other automatic differentiation frameworks (Chainer, Torch, Theano, etc.) operate on gradient descent of smooth functions. If you can

In general, TensorFlow and other automatic differentiation frameworks (Chainer, Torch, Theano, etc.) operate on gradient descent of smooth functions. If you can recast your combinatorial problem into a smooth function, then these frameworks may be applicable. However, most combinatorial optimization problems aren't readily transformed into smooth functions, so this is unlikely to be straightforward.