420 several thousands of nodes) and on dense graphs, while \ref CostScaling is |
420 several thousands of nodes) and on dense graphs, while \ref CostScaling is |
421 typically more efficient on large graphs (e.g. hundreds of thousands of |
421 typically more efficient on large graphs (e.g. hundreds of thousands of |
422 nodes or above), especially if they are sparse. |
422 nodes or above), especially if they are sparse. |
423 However, other algorithms could be faster in special cases. |
423 However, other algorithms could be faster in special cases. |
424 For example, if the total supply and/or capacities are rather small, |
424 For example, if the total supply and/or capacities are rather small, |
425 \ref CapacityScaling is usually the fastest algorithm (without effective scaling). |
425 \ref CapacityScaling is usually the fastest algorithm |
|
426 (without effective scaling). |
426 |
427 |
427 These classes are intended to be used with integer-valued input data |
428 These classes are intended to be used with integer-valued input data |
428 (capacities, supply values, and costs), except for \ref CapacityScaling, |
429 (capacities, supply values, and costs), except for \ref CapacityScaling, |
429 which is capable of handling real-valued arc costs (other numerical |
430 which is capable of handling real-valued arc costs (other numerical |
430 data are required to be integer). |
431 data are required to be integer). |