Perhaps this may seem odd to hear in a THG forum, but I've worked on an NP problem described by Scott Aaronson (the 3-color map problem) and found that a combination intelligent tree pruning and statistical search indexing yields a yes/no result in a time-frame that is not NP. I've only tested this on smaller maps (50 US states), so I could be wrong with much larger maps. Here is what Scott says (if your still interested):
"But what about NP? Contrary to widespread belief, NP does not stand for “Non
Polynomial-Time,” but for a technical concept called “Nondeterministic Polynomial-
Time.” (Yes, I know: when it comes to weird acronyms, computer scientists could put
any Pentagon office to shame.) You can think of NP as the class of problems for which a
valid solution can be recognized in polynomial time. For example, let’s say you wanted
to color a map with three colors, so that no two countries sharing a border were colored
the same [see Figure]. With only a few countries, this is easy to do by trial and error, but
as more countries are added, the number of possible colorings becomes astronomical. On
the other hand, if you simply gave the coloring job to your grad student, then when the
answer came back after the end of eternity, you could quickly tell whether or not your
student had succeeded: you’d just have to look at the map, and check whether any two
neighboring countries were colored the same. This is why the map-coloring problem is
in NP."