  Previously, transport networks are usually treated as homogeneous networks,
that is, every node has the same function, simultaneously providing and
requiring resources. However, some real networks, such as power grid and supply
chain networks, show a far different scenario in which the nodes are classified
into two categories: the supply nodes provide some kinds of services, while the
demand nodes require them. In this paper, we propose a general transport model
for those supply-demand networks, associated with a criterion to quantify their
transport capacities. In a supply-demand network with heterogenous degree
distribution, its transport capacity strongly depends on the locations of
supply nodes. We therefore design a simulated annealing algorithm to find the
optimal configuration of supply nodes, which remarkably enhances the transport
capacity, and outperforms the degree target algorithm, the betweenness target
algorithm, and the greedy method. This work provides a start point for
systematically analyzing and optimizing transport dynamics on supply-demand
networks.
