  We present a provably more efficient implementation of the Minimum Norm Point
Algorithm conceived by Fujishige than the one presented in \cite{FUJI06}. The
algorithm solves the minimization problem for a class of functions known as
submodular. Many important functions, such as minimum cut in the graph, have
the so called submodular property \cite{FUJI82}. It is known that the problem
can also be efficiently solved in strongly polynomial time \cite{IWAT01},
however known theoretical bounds are far from being practical. We present an
improved implementation of the algorithm, for which unfortunately no worst case
bounds are know, but which performs very well in practice. With the
modifications presented, the algorithm performs an order of magnitude faster
for certain submodular functions.
