A faster and simpler strongly polynomial time algorithm for submodular function minimization

A submodular function f is a set valued function defined  on a set V such that
for all subsets S and T of V, f(S) + f(T) >= f(S  union T) + f(S intersection T).  We
consider the problem of  Submodular Function Minimization (SFM).  We provide an overview
on  the significance of submodular function minimization in combinatorial  optimization,
and survey previous polynomial time algorithms for  solving this problem.  We also
present a new algorithm that runs in O (n^5 Q + n^6) steps, where Q is the time it takes
to evaluate f( ).   The algorithm improves upon the best previous combinatorial strongly 
polynomial algorithm by a factor of n log n, and also strictly  dominates the running
time of the ellipsoid algorithm on SFM.