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.