several thousands of nodes) and on dense graphs, while \ref CostScaling is

 several thousands of nodes) and on dense graphs, while \ref CostScaling is

 typically more efficient on large graphs (e.g. hundreds of thousands of

 typically more efficient on large graphs (e.g. hundreds of thousands of

 nodes or above), especially if they are sparse.

 nodes or above), especially if they are sparse.

 However, other algorithms could be faster in special cases.

 However, other algorithms could be faster in special cases.

 For example, if the total supply and/or capacities are rather small,

 For example, if the total supply and/or capacities are rather small,

 These classes are intended to be used with integer-valued input data

 These classes are intended to be used with integer-valued input data

 (capacities, supply values, and costs), except for \ref CapacityScaling,

 (capacities, supply values, and costs), except for \ref CapacityScaling,

 which is capable of handling real-valued arc costs (other numerical

 which is capable of handling real-valued arc costs (other numerical

 data are required to be integer).

 data are required to be integer).