I'm gonna give you a (somewhat small) version (although comprehensible, I think) of a scientific proof that you cannot do this under a feasible amount of time.
What I'm gonna prove is that the time complexity to enumerate all simple paths between two selected and distinct nodes (say, s
and t
) in an arbitrary graph G
is not polynomial. Notice that, as we only care about the amount of paths between these nodes, the edge costs are unimportant.
Sure that, if the graph has some well selected properties, this can be easy. I'm considering the general case though.
Suppose that we have a polynomial algorithm that lists all simple paths between s
and t
.
If G
is connected, the list is nonempty. If G
is not and s
and t
are in different components, it's really easy to list all paths between them, because there are none! If they are in the same component, we can pretend that the whole graph consists only of that component. So let's assume G
is indeed connected.
The number of listed paths must then be polynomial, otherwise the algorithm couldn't return me them all. If it enumerates all of them, it must give me the longest one, so it is in there. Having the list of paths, a simple procedure may be applied to point me which is this longest path.
We can show (although I can't think of a cohesive way to say it) that this longest path has to traverse all vertices of G
. Thus, we have just found a Hamiltonian Path with a polynomial procedure! But this is a well known NP-hard problem.
We can then conclude that this polynomial algorithm we thought we had is very unlikely to exist, unless P = NP.