doc/groups.dox
changeset 1026 699c7eac2c6d
parent 1002 f63ba40a60f4
child 1038 a2d142bb5d3c
equal deleted inserted replaced
49:828dd12f1aa3 50:417ab2c5a98f
   405    shortest path method \ref edmondskarp72theoretical.
   405    shortest path method \ref edmondskarp72theoretical.
   406  - \ref CycleCanceling Cycle-Canceling algorithms, two of which are
   406  - \ref CycleCanceling Cycle-Canceling algorithms, two of which are
   407    strongly polynomial \ref klein67primal, \ref goldberg89cyclecanceling.
   407    strongly polynomial \ref klein67primal, \ref goldberg89cyclecanceling.
   408 
   408 
   409 In general, \ref NetworkSimplex and \ref CostScaling are the most efficient
   409 In general, \ref NetworkSimplex and \ref CostScaling are the most efficient
   410 implementations, but the other algorithms could be faster in special cases.
   410 implementations.
       
   411 \ref NetworkSimplex is usually the fastest on relatively small graphs (up to
       
   412 several thousands of nodes) and on dense graphs, while \ref CostScaling is
       
   413 typically more efficient on large graphs (e.g. hundreds of thousands of
       
   414 nodes or above), especially if they are sparse.
       
   415 However, other algorithms could be faster in special cases.
   411 For example, if the total supply and/or capacities are rather small,
   416 For example, if the total supply and/or capacities are rather small,
   412 \ref CapacityScaling is usually the fastest algorithm (without effective scaling).
   417 \ref CapacityScaling is usually the fastest algorithm (without effective scaling).
   413 
   418 
   414 These classes are intended to be used with integer-valued input data
   419 These classes are intended to be used with integer-valued input data
   415 (capacities, supply values, and costs), except for \ref CapacityScaling,
   420 (capacities, supply values, and costs), except for \ref CapacityScaling,