  Consider a transportation problem with sets of sources and sinks. There are
profits and prices on the edges. The goal is to maximize the profit while
meeting the following constraints; the total flow going out of a source must
not exceed its capacity and the total price of the incoming flow on a sink must
not exceed its budget. This problem is closely related to the generalized flow
problem.
  We propose an auction based primal dual approximation algorithm to solve the
problem. The complexity is $O(\epsilon^{-1}(n^2+ n\log{m})m\log U)$ where $n$
is the number of sources, $m$ is the number of sinks, $U$ is the ratio of the
maximum profit/price to the minimum profit/price.
  We also show how to generalize the scheme to solve a more general version of
the problem, where there are edge capacities and/or the profit function is
concave and piece-wise linear. The complexity of the algorithm depends on the
number of linear segments, termed ${\cal L}$, of the profit function.
