There are many approaches to optimizing systems, and two-probes are particularly tricky since they are made up of several parts.
The simplest, but also most time-consuming way is to make us of the equivalent bulk, as discussed above. Another is to pre-optimize the individual parts and then assume that nothing much happens when they are put together. For instance, if your problem is a nanotube with a defect, between metal electrodes, you may want to simplify the problem by optimizing the defect locally, in a smaller nanotube setting, and then assume the rest of the tube + the metal surfaces are perfect.
Or, if the contact properties of a nanotube with a metal surface are under investigation, you may assume that the tube and the surface are intact themselves, but their relative position may change. In this case you have to move the tube around on the surface in a clever, systematic way, to find the optimum. Or, as is probably more relevant, simply move it around more or less at random and do many calculations of the current, and then do a statistical analysis of the results (the current, for instance), since the real position of such a tube/metal interface will probably not be absolutely stable in an experimental setting anyway.
And so on